170 accepted papers
Flow-based generative models can be viewed through a physics lens: sampling transports a particle from noise to data by integrating a time-varying velocity field, and each sample corresponds to a trajectory with its own dynamical effort. Motivated by classical mechanics, we introduce Kinetic Path En…
Aerial manipulation requires force-aware capabilities to enable safe and effective grasping and physical interaction. Previous works often rely on heavy, expensive force sensors unsuitable for typical quadrotor platforms, or perform grasping without force feedback, risking damage to fragile objects.…
Extrinsic calibration for LiDAR and camera using sparse point clouds can significantly reduce cost and improve efficiency. However, most target-based methods are designed for dense point clouds and are less effective in sparse scenarios, while targetless methods primarily rely on environmental featu…
Terrestrial-aerial bimodal vehicles, which integrate the high mobility of aerial robots with the long endurance of ground robots, offer significant potential for autonomous exploration. Given the inherent energy and time constraints in practical exploration tasks, we present a hierarchical framework…
Coaxial bi-copter autonomous aerial vehicles (AAVs) have garnered attention due to their potential for improved rotor system efficiency and compact form factor. However, balancing efficiency, maneuverability, and compactness in coaxial bi-copter systems remains a key design challenge, limiting their
Coaxial bi-copter unmanned aerial vehicles (UAVs) have garnered attention due to their potential for improved rotor system efficiency and compact form factor. However, balancing efficiency, maneuverability, and compactness in coaxial bi-copter systems remains a key design challenge, limiting their p…
Due to the difficulties of directly obtaining high-resolution hyperspectral images (HR-HSI), the fusion of low-resolution hyperspectral images (LR-HSI) and high-resolution multispectral images (HR-MSI) has emerged as an effective approach. While existing methods leverage image-level priors from HR-M
Existing motion planning methods often struggle with rapid-motion obstacles due to an insufficient understanding of environmental changes. To address this, we propose integrating motion planners with Doppler LiDARs, which provide not only ranging measurements but also instantaneous point velocities.
This paper aims to bridge perception and planning in navigation systems by learning optimal trajectories from depth information in an end-to-end fashion. However, using neural networks as black-box replacements for traditional modules risks scalability and adaptability. Moreover, such methods often …
Navigation is a fundamental capability in embodied AI, representing the intelligence required to perceive and interact within physical environments. To achieve such intelligence, recent advanced works leverage Vision-Language Models (VLMs), which demonstrate strong generalizability and possess a wel…
Underwater environments impose severe challenges to visual-inertial odometry systems, as strong light attenuation, marine snow and turbidity, together with weakly exciting motions, degrade inertial observability and cause frequent tracking failures over long-term operation. While tightly coupled aco
Convex polytopes have compact representations and exhibit convexity, which makes them suitable for abstracting obstacle-free spaces from various environments. Existing generation methods struggle with balancing high-quality output and efficiency. Moreover, another crucial requirement for convex poly…
In this paper, we propose FastViDAR, a novel framework that takes four fisheye camera inputs and produces a full 360 depth map along with per-camera depth, fusion depth, and confidence estimates. Our main contributions are: (1) We introduce Alternative Hierarchical Attention (AHA) mechanism that eff…
Modern autonomous navigation systems predominantly rely on lidar and depth cameras. However, a fundamental question remains: Can flying robots navigate in clutter using solely monocular RGB images? Given the prohibitive costs of real-world data collection, learning policies in simulation offers a pr
Lower-limb exoskeleton robots play a significant role in both rehabilitation and assisted walking, where accurate prediction of lower-limb joint angles is crucial for achieving natural gait. However, due to inter-subject variability and differences across locomotion modes, achieving cross-task gener…
Reconstructing large-scale RGB point clouds is an important task in robotics, supporting perception, navigation, and scene understanding. Despite advances in LiDAR inertial visual odometry (LIVO), its performance remains highly sensitive to extrinsic calibration. Meanwhile, 3D vision foundation mode
The new era has witnessed a remarkable capability to extend Vision-Language Models (VLMs) for tackling tasks of video understanding. While current VLMs excel at event- or story-level understanding, their ability to capture fine-grained motion details remains limited, primarily due to their focus on
While data augmentation is essential for robust point cloud recognition, conventional spatial mixup strategies often compromise geometric integrity by generating physically unrealistic samples. To overcome this limitation, we propose PSMix, which shifts the mixing paradigm to the spectral domain via…
Thermal infrared (TIR) 3D reconstruction provides geometry that is intrinsically coupled to the temperature field, even in low-light, nighttime, and smoke-obscured environments. TIR imaging measures self-emitted thermal radiation driven by object temperature and is largely independent of external il
Due to the limited online computational resources and the inherent probability of hardware and software failures of real-world robots, large-scale formation planning faces two common challenges: computational intractability and agent failures. Based on the theory of sparse graphs and the maximum cli…
Although Federated Learning (FL) offers advantages in privacy-preserving for cross-device collaborative learning, its practical deployment remains severely constrained by heterogeneous hardware resources and non-IID (non-independent and identically distributed) data across devices. Sub-model extract…
The growing industrial demand for customized and cost-efficient large language models (LLMs) is fueled by the rise of vertical, domain-specific tasks and the need to optimize performance under constraints such as latency and budget. Knowledge distillation, as an efficient model compression and trans
Optimization has been widely used to generate smooth trajectories for motion planning. However, existing trajectory optimization methods show weakness when dealing with large-scale long trajectories. Recent advances in parallel computing have accelerated optimization in some fields, but how to effic…
Differential drive mobile manipulators combine the mobility of wheeled bases with the manipulation capability of multi-joint arms, enabling versatile applications but posing considerable challenges for trajectory planning due to their high-dimensional state space and nonholonomic constraints. This p…
Differential drive robots are widely used in various scenarios thanks to their straightforward principle, from household service robots to disaster response field robots. The nonholonomic dynamics and possible lateral slip of these robots lead to difficulty in getting feasible and high-quality traje…
Precise extrinsic calibration is one of the key techniques for LiDAR-camera fusion system. In current methods, the extrinsic calibration is usually not automatic. To address this, an automatic calibration method via combining semantic and geometric features is proposed, which is not dependent on any…
Existing robotic trajectory planning frameworks typically approximate the robot’s geometry and environmental constraints. While this improves computational efficiency, it sacrifices the solution space and frequently encounters failure in confined environments. However, attaining a precise geometric
Performing striking aerobatic flight in complex environments demands manual designs of key maneuvers in advance, which is intricate and time-consuming as the horizon of the trajectory performed becomes long. This paper presents a novel framework that leverages diffusion models to automate and scale
Terrestrial-aerial bimodal vehicles, which integrate the high mobility of aerial robots with the long endurance of ground robots, offer significant potential for autonomous exploration. Given the inherent energy and time constraints in practical exploration tasks, we present a hierarchical framework
Three-dimensional (3D) medical images, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are essential for clinical applications. However, the need for diverse and comprehensive representations is particularly pronounced when considering the variability across different organs,…
Recently, there has been growing interest in using low-cost sensor combinations, such as cameras and IMUs, to achieve accurate localization within pre-built pointcloud maps. In this paper, we propose a novel hybrid visual-Lidar mapping and visual-only re-localization framework, specifically designed
Emotion recognition in conversations (ERC) has garnered significant attention from the research community. However, due to the complexity of visual scenes and dialogue contextual dependencies in conversations, previous ERC methods fail to handle emotional cues from both visual sources and discourse…
End-to-end learning has emerged as a transformative paradigm for autonomous driving. However, the inherently multimodal nature of driving behaviors remains a fundamental challenge to robust deployment. We propose DiffE2E, a diffusion-based end-to-end autonomous driving framework. The architecture fi…
This paper aims to bridge perception and planning in navigation systems by learning optimal trajectories from depth information in an end-to-end fashion. However, using neural networks as black-box replacements for traditional modules risks scalability and adaptability. Moreover, such methods often
Terrestrial-aerial bimodal vehicles (TABVs) can fly to avoid obstacles and move safely on the ground to save energy, offering enhanced adaptability and flexibility in various challenging environments. However, a robust localization approach becomes a bottleneck to stably applying the TABVs in real-w
With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have rapidly developed, the challenge remains to generate efficient,
Pneumatic soft robots offer outstanding flexibility and safety in human-robot interactions. However, achieving full integration requires air sources that are not only highly flexible but also lightweight. Existing soft air pumps are often constrained by structural limitations and inadequate output p
Coordinate initialization is the first step in accomplishing collaborative tasks within robot swarms, determining the quality of tasks. However, fast and robust coordinate initialization in vision-based drone swarms remains elusive. To this end, our letter proposes a complete system for initial rela
How to endow aerial robots with the ability to operate in close proximity remains an open problem. The core challenges lie in the propulsion system’s dual-task requirement: generating manipulation forces while simultaneously counter-acting gravity. These competing demands create dynamic coupling eff
A long-cherished vision of drones is to autonomously traverse through clutter to reach every corner of the world using onboard sensing and computation. In this paper, we combine onboard 3D lidar sensing and sim-to-real reinforcement learning (RL) to enable autonomous flight in cluttered environments
CoNi-MPC [1] provides an efficient framework for UAV control in air-ground cooperative tasks by relying exclusively on relative states, eliminating the need for global state estimation. However, its lack of environmental information poses significant challenges for obstacle avoidance. To address thi
In complex missions such as search and rescue, robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances situational awareness and is crucial for intelligent robotics. Tra
Infrared small target detection (IRSTD) focuses on identifying small targets in infrared images. Despite advancements with deep learning, challenges persist due to the IR long-range imaging mechanism, where targets are small, dim, and easily lost in noise and background clutter. Current deep learnin…
Large language models (LLMs) have garnered increasing attention owing to their powerful comprehension and generation capabilities. Generally, larger LLMs (L-LLMs) that require paid interfaces exhibit significantly superior performance compared to smaller LLMs (S-LLMs) that can be deployed on a varie
Visual Emotion Analysis (VEA) seeks to anticipate individuals’ emotional reactions to visual stimuli. The subjective perception of visual emotion is an integrated impact of the appearance, scene, and objects presented in an image. It is thus significance to analysis visual emotion by incorporating d…
In the field of Moving Infrared Small Target Detection (MIRSTD), current methods typically use sequential modeling with two individual modules for spatial and temporal processing. However, such a modeling strategy lacks clear guidance on the motion and displacement difference between moving targets…
The objective of snapshot spectral compressive imaging reconstruction is to recover the 3D hyperspectral image (HSI) from a 2D measurement. Existing methods either focus on network architecture design or simply introduce image-level prior to the model. However, these methods lack guiding information
Although deep neural networks have achieved remarkable success in various computer vision tasks, they face significant challenges in degraded image understanding due to domain shifts caused by quality variations. Drawing biological inspiration from the human visual system (HVS), which dynamically ad…
Advanced Deep Neural Networks (DNNs) perform well for high-quality images, but their performance dramatically decreases for degraded images. Data augmentation is commonly used to alleviate this problem, but using too much perturbed data might seriously decrease the performance on pristine images. To…
Terrain analysis is critical for the practical application of ground mobile robots in real-world tasks, especially in outdoor unstructured environments. In this paper, we propose a novel spatial-temporal traversability assessment method, which aims to enable autonomous robots to effectively navigate
Infrared Small Target Detection (IRSTD) aims to identify low signal-to-noise ratio small targets in infrared images with complex backgrounds, which is crucial for various applications. However, existing IRSTD methods typically rely solely on image modalities for processing, which fail to fully captu…
Autonomous navigation of car-like robots on uneven terrain poses unique challenges compared to flat terrain, particularly in traversability assessment and terrain-associated kinematic modelling for motion planning. This paper introduces SEB-Naver, a novel SE(2)-based local navigation framework desig
Dynamic jumping on high platforms and over gaps differentiates legged robots from wheeled counterparts. Compared to walking on rough terrains, dynamic locomotion on abrupt surfaces requires fusing proprioceptive and exteroceptive perception for explosive movements. In this paper, we propose SF-TIM (
End-to-end autonomous driving, which directly maps raw sensor inputs to low-level vehicle controls, is an crucial part of Embodied AI. Despite successes in applying Multimodal Large Language Models (MLLMs) for high-level traffic scene semantic understanding, it remains challenging to effectively tra
Single-frame Infrared Small Target (SIRST) detection has made significant advancements, but it still faces challenges due to limited labeled data and the foreground-background class imbalance. To address these issues, we introduce a novel Semi-Supervised SIRST Detection (S^3D) pipeline in this paper…
Drones have become essential in various applications, but conventional quadrotors face limitations in confined spaces and complex tasks. Deformable drones, which can adapt their shape in real-time, offer a promising solution to overcome these challenges, while also enhancing maneuverability and enab
Optimization has been widely used to generate smooth trajectories for motion planning. However, existing trajectory optimization methods show weakness when dealing with large-scale long trajectories. Recent advances in parallel computing have accelerated optimization in some fields, but how to effic
This paper focuses on Dialogue Aspect-based Sentiment Quadruple (DiaASQ) analysis, aiming to extract structured quadruples from multi-turn conversations. Applying Large Language Models (LLMs) for this specific task presents two primary challenges: the accurate extraction of multiple elements and the
Achieving coordinated teamwork among legged robots requires both fine-grained locomotion control and long-horizon strategic decision-making. Robot soccer offers a compelling testbed for this challenge, combining dynamic, competitive, and multi-agent interactions. In this work, we present a hierarchi…
Terrestrial and aerial bimodal vehicles have gained significant interest due to their energy efficiency and versatile maneuverability across different domains. However, most existing passive-wheeled bimodal vehicles rely on attitude regulation to generate forward thrust, which inevitably results in
Flying through body-size narrow gaps in the environment is one of the most challenging moments for an underactuated multirotor. We explore a purely data-driven method to master this flight skill in simulation, where a neural network directly maps pixels and proprioception to continuous low-level con
Drone racing has become a popular international competition and has attained wide attention in recent years. However, the requirements of high-level operation keep the novice pilots away from participating in it. This paper presents a trajectory-based flight assistive system that enables various ope…
Collision is typically avoided in robot navigation for safety guarantee. However, when a robot’s exteroceptive sensors fail, which means it becomes "blind", collision can actually be leveraged to improve localization performance. Our research demonstrates the informative nature of collisions in this…
Perception is necessary for autonomous navigation in an unknown area crowded with obstacles. It’s challenging for a robot to navigate safely without any sensors that can sense the environment, resulting in a blind robot, and becomes more difficult when comes to a group of robots. However, it could b…
Multi-robot teams have attracted attention from industry and academia for their ability to perform collaborative tasks in unstructured environments, such as wilderness rescue and collaborative transportation. In this letter, we propose a trajectory planning method for a non-holonomic robotic team wi
Multi-robot system is desired to achieve global cost-efficiency by fully utilizing individual advantages. For example, leveraging unmanned aerial vehicles' (UAVs') agility for inspection and ground vehicles' (UGVs') capability for heavy-duty tasks. Coordinating the motion of multiple robots smartly
Accurate human motion prediction is vital for diverse artificial intelligence applications, and recent research has yielded substantial advancements. Despite this, the prediction process often encounters abrupt discontinuities and accumulates errors over the long term due to insufficient modeling of…
The classification problem of multivariate time series has been widely used in many fields, but current methods still cannot achieve high accuracy. In this paper, a novel multivariate time series classification model named FDNet (Feature and Difference encoding fused Network) is proposed. A structur…
State-of-the-art robotics simulators are equipped with well-established mapping, planning, and control systems. However, they lack modularity and the convenience of plug-and-play functionality. In this work, we present FastSim, a high-fidelity and user-friendly simulation framework based on the Unit
In many situations such as city delivery and wild inspection, quadrotors are often required to follow a predefined reference trajectory. However, these reference trajectories cannot be perfectly safe, resulting in conflicts between tracking the reference precisely, flying safely, and finishing the m…
Active reconstruction technique enables robots to autonomously collect scene data for full coverage, relieving users from tedious and time-consuming data capturing process. However, designed based on unsuitable scene representations, existing methods show unrealistic reconstruction results or the in…
In this paper we explore a novel challenging generation task i.e. Handwritten Mathematical Expression Generation (HMEG) from symbolic sequences. Since symbolic sequences are naturally graph-structured data we formulate HMEG as a graph-to-image (G2I) generation problem. Unlike the generation of natur…
Handling graph data is one of the most difficult tasks. Traditional techniques, such as those based on geometry and matrix factorization, rely on assumptions about the data relations that become inadequate when handling large and complex graph data. On the other hand, deep learning approaches demons…
In this paper, we present a novel system for Human-Robot Interactive Creation of Artworks (HRICA). Different from previous robot painters, HRICA allows a human user and a robot to alternately draw strokes on a canvas, to collaboratively create a portrait drawing through frequent interactions. The ke…
Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can…
Just as humans can become disoriented in featureless deserts or thick fogs, not all environments are conducive to the Localization Accuracy and Stability (LAS) of autonomous robots. This paper introduces an efficient framework designed to enhance LiDAR-based LAS through strategic trajectory generati…
In this paper, we propose an unsupervised artistic portrait drawing generation method for few-shot datasets based on contrastive learning of style features. Firstly, we construct a discriminative style encoder with contrastive learning, improving the ability of the encoder to separate style features…
Animals learn to adapt speed of their movements to their capabilities and the environment they observe. Mobile robots should also demonstrate this ability to trade-off aggressiveness and safety for efficiently accomplishing tasks. The aim of this work is to endow flight vehicles with the ability of
In recent years, multirotors have become more and more widely used, such as in aerial photography and delivery. Ensuring a safe landing in emergencies is the most basic requirement, and it is important to make full use of all the sensors of the multirotor. To improve the safety of UAV landing in unk…
The excellent swimming ability of fish provides a new solution for the design of underwater propellers. However, there is a lack of optimization schemes for the structure and performance of the continuum driving fish-like propeller. This letter introduces, for the first time, a continuum driving fis
Relative state estimation is crucial for vision-based swarms to estimate and compensate for the unavoidable drift of visual odometry. For autonomous drones equipped with the most compact sensor setting — a stereo camera that provides a limited field of view (FoV), the demand for mutual observation f…
Mobile manipulators have recently gained significant attention in the robotics community due to their superior potential in industrial and service applications. However, the high degree of freedom associated with mobile manipulators poses challenges in achieving real-time whole-body motion planning.…
This paper explores the distance-based relative state estimation problem in large-scale systems, which is hard to solve effectively due to its high-dimensionality and non-convexity. In this paper, we alleviate this inherent hardness to simultaneously achieve scalability and robustness of inference o…
Mutual localization stands as a foundational component within various domains of multi-robot systems. Nevertheless, in relative pose estimation, time synchronization is usually underappreciated and rarely addressed, although it significantly influences estimation accuracy. In this paper, we introduc…
In this letter, we present a novel bi-modal bi-copter robot called Skater, which is adaptable to air and various ground surfaces. Skater consists of a bi-copter moving along its longitudinal direction with two passive wheels on both sides. Using a longitudinally arranged bi-copter as the unified act
This paper tackles the challenge of autonomous target search using unmanned aerial vehicles (UAVs) in complex unknown environments. To fill the gap in systematic approaches for this task, we introduce Star-Searcher, an aerial system featuring specialized sensor suites, mapping, and planning modules
Millimeter wave (mmWave) radars have attracted significant attention from both academia and industry due to their capability to operate in extreme weather conditions. However, they face challenges in terms of sparsity and noise interference, which hinder their application in the field of micro aeria
Recently, significant progress has been made in few-shot segmentation (FSS), which aims to segment unknown objects with only a few support images. However, during both training and testing, FSS still requires pixel-level annotations. When only image-level labels are available, FSS will become a more…
We propose a robust framework for planar pose graph optimization contaminated by loop closure outliers. Our framework rejects outliers by first decoupling the robust PGO problem wrapped by a Truncated Least Squares kernel into two subproblems. Then, the framework introduces a linear angle representa…
Collision evaluation is of essential importance in various applications. However, existing methods are either cumbersome to calculate or not exact. Therefore, considering the cost of implementation, most whole-body planning works, which require evaluating collision between robots and environments, s…
Autonomous navigation of ground robots on uneven terrain is being considered in more and more tasks. However, uneven terrain will bring two problems to motion planning: how to assess the traversability of the terrain and how to cope with the dynamics model of the robot associated with the terrain. T…
The advance of unmanned aerial vehicles (UAVs) has enabled customers and directors to film from the air. However, operating the drone to produce desired videos upon a moving object is hard to achieve. This letter proposes an autonomous aerial videography system that integrates customized shots and d
The robotics community is increasingly interested in autonomous aerial transportation. Unmanned aerial vehicles with suspended payloads have advantages over other systems, including mechanical simplicity and agility, but pose great challenges in planning and control. To realize fully autonomous aeri
In this letter, an aggressive quadrotor ball playing system called Bat is proposed, whose goal is to intercept a flying ball and volley it towards a designated target. Aggressive means Bat operates the quadrotor aggressively to intercept balls that are far away and hit them to distant positions in w
Mutual localization provides a consensus of reference frame as an essential basis for cooperation in multi-robot systems. Previous works have developed certifiable and robust solvers for relative transformation estimation between each pair of robots. However, recovering relative poses for robotic sw
Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye c…
The development of autonomous rotary-wing UAVs has shown an evident tendency in miniaturization. However, the side effects brought by miniaturization, such as decreased load capability, shorter flight duration and reduced autonomous ability, seriously hinder its process. In this paper, we first inve…
This letter presents a novel solution for UAV control in cooperative multi-robot systems, which can be used in various scenarios such as leader-following, landing on a moving base, or specific relative motion with a target. Unlike classical methods that tackle UAV control in the world frame, we dire
Optimization-based trajectory generation methods are widely used in whole-body planning for robots. However, existing work either oversimplifies the robot's geometry and environment representation, resulting in a conservative trajectory or suffers from a huge overhead in maintaining additional infor…
Robot swarm is a hot spot in robotic research community. In this paper, we propose a decentralized framework for car-like robotic swarm which is capable of real-time planning in cluttered environments. In this system, path finding is guided by environmental topology information to avoid frequent top…
Implicit neural representations have shown promising potential for 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain for view path planning. Effective as it is, the computation of the information gain is expensive, and compared with that usi…
Facial sketch synthesis (FSS) aims to generate a vivid sketch portrait from a given facial photo. Existing FSS methods merely rely on 2D representations of facial semantic or appearance. However, professional human artists usually use outlines or shadings to covey 3D geometry. Thus facial 3D geometr…
We present a novel framework for exemplar based image translation. Recent advanced methods for this task mainly focus on establishing cross-domain semantic correspondence, which sequentially dominates image generation in the manner of local style control. Unfortunately, cross domain semantic matchin…
Terrestrial and aerial bimodal vehicles have gained widespread attention due to their cross-domain maneuverability. Nevertheless, their bimodal dynamics significantly increase the complexity of motion planning and control, thus hindering robust and efficient autonomous navigation in unknown environm…
In recent years, there is a noteworthy advance-ment in autonomous drone racing. However, the primary focus is on attaining execution times, while scant attention is given to the challenges of dynamic environments. The high-speed nature of racing scenarios, coupled with the potential for unforeseeabl…
Autonomous UAV path planning for 3D reconstruction has been actively studied in various applications for high-quality 3D models. However, most existing works have adopted explore-then-exploit, prior-based or exploration-based strategies, demonstrating inefficiency with repeated flight and low autono…
This letter presents a novel and retractable ring-shaped quadrotor called Ring-Rotor that can adjust the vehicle's length and width simultaneously. Unlike other morphing quadrotors with high platform complexity and poor controllability, Ring-Rotor uses only one servo motor for morphing but reduces t
For letting mobile robots travel flexibly through complicated environments, increasing attention has been paid to the whole-body collision evaluation. Most existing works either opt for the conservative corridor-based methods that impose strict requirements on the corridor generation, or ESDF-based…
The Roller-Quadrotor is a novel quadrotor that combines the maneuverability of aerial drones with the endurance of ground vehicles. This work focuses on the design, modeling, and experimental validation of the Roller-Quadrotor. Flight capabilities are achieved through a quadrotor config-uration, wit…
In constrained solution spaces with a huge number of homotopy classes, standalone sampling-based kinodynamic planners suffer low efficiency in convergence. Local optimization is integrated to alleviate this problem. In this paper, we propose to thrive the trajectory tree growing by optimizing the tr…
Neural radiance fields (NeRF) based methods have shown amazing performance in synthesizing 3D-consistent photographic images, but fail to generate multi-view portrait drawings. The key is that the basic assumption of these methods -- a surface point is consistent when rendered from different views -…
By taking the complementary advantage of multicopters and ground vehicles, air-ground vehicles have shown great potential in various fields due to their superior mobility and outstanding endurance. However, most of the previous works adopt complicated mechanisms, and fail to develop a controller wit
Operating unmanned aerial vehicles (UAVs) in complex environments that feature dynamic obstacles and external disturbances poses significant challenges, primarily due to the inherent uncertainty in such scenarios. Additionally, inaccurate robot localization and modeling errors further exacerbate the…
With the development of robotics, ground robots are no longer limited to planar motion. Passive height variation due to complex terrain and active height control provided by special structures on robots require a more general navigation planning framework beyond 2D. Existing methods rarely considers…
Service robots have attracted extensive attention due to specially designed functions, such as mobile manipulators or robots with extra structures. For robots that have changing shapes, autonomous navigation in the real world presents new challenges. In this paper, we propose a trajectory optimizati…
Online trajectory planners enable quadrotors to safely and smoothly navigate in unknown cluttered environments. However, tuning parameters is challenging since modern planners have become too complex to mathematically model and predict their interaction with unstructured environments. This work take…
Terrestrial-aerial bimodal vehicles bloom in both academia and industry because they incorporate both the high mobility of aerial vehicles and the long endurance of ground vehicles. In this work, we present an autonomous and adaptive navigation framework to bring complete autonomy to this class of v
Quadrotors are agile platforms. With human experts, they can perform extremely high-speed flights in cluttered environments. However, fully autonomous flight at high speed remains a significant challenge. In this work, we propose a motion planning algorithm based on the corridor-constrained minimum…
Mutual localization is essential for coordination and cooperation in multi-robot systems. Previous works have tackled this problem by assuming available correspondences between measurements and received odometry estimations. However, the correspondence is difficult to acquire, especially for unified
In this work, we propose an interoceptive-only state estimation system for a quadrotor with deep neural network processing, where the quadrotor dynamics is considered as a perceptive supplement of the inertial kinematics. To improve the precision of multi-sensor fusion, we train cascaded networks on
Disease-related representations play a crucial role in image-based disease prediction such as cancer diagnosis, due to its considerable generalization capacity. However, it is still a challenge to identify lesion characteristics in obscured images, as many lesions are obscured by other tissues. In t…
For aerial swarms, navigation in a prescribed formation is widely practiced in various scenarios. However, the associated planning strategies typically lack the capability of avoiding obstacles in cluttered environments. To address this deficiency, we present an optimization-based method that ensure…
Free-space-oriented roadmaps typically generate a series of convex geometric primitives, which constitute the safe region for motion planning. However, a static environment is assumed for this kind of roadmap. This assumption makes it unable to deal with dynamic obstacles and limits its applications…
For real-time multirotor kinodynamic planning, the efficiency of sampling-based methods is usually hindered by difficult-to-sample homotopy classes like narrow passages. In this paper, we address this issue by a hybrid scheme. We firstly propose a fast regional optimizer exploiting the information o…
This paper proposes Elastic Tracker, a flexible trajectory planning framework that can deal with challenging tracking tasks with guaranteed safety and visibility. Firstly, an object detection and intension-free motion prediction method is designed. Then an occlusion-aware path finding method is prop…
Designing autonomous aerial robot team systems remains a grand challenge in robotics. Existing works in this field can be categorized as centralized and decentralized. Centralized methods suffer from scale dilemmas, while decentralized ones often lead to poor planning quality. In this paper, we prop
Gaze isan intuitive and direct way to represent the intentions of an individual. However, when it comes to assistive aerial teleoperation which aims to perform operators’ intention, rare attention has been paid to gaze. Existing methods obtain intention directly from the remote controller (RC) input
Visual-inertial-odometry has attracted extensive attention in the field of autonomous driving and robotics. The size of Field of View (FoV) plays an important role in Visual-Odometry (VO) and Visual-Inertial-Odometry (VIO), as a large FoV enables to perceive a wide range of surrounding scene element…
This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exp…
Predicting stochastic spreading processes on complex networks is critical in epidemic control, opinion propagation, and viral marketing. We focus on the problem of inferring the time-dependent marginal probabilities of states for each node which collectively quantifies the spreading results. Dynamic…
This paper presents a novel trajectory planning method for aerial perching. Compared with the existing work, the terminal states and the trajectory durations can be adjusted adaptively, instead of being determined in advance. Further-more, our planner is able to minimize the tangential relative spee…
In this paper, we describe a robust multi-drone planning framework for high-speed trajectories in large scenes. It uses a free-space-oriented map to free the optimization from cumbersome environment data. A capsule-like safety constraint is designed to avoid reciprocal collisions when vehicles devia…
The visible capability is critical in many robot applications, such as inspection and surveillance, etc. Without the assurance of the visibility to targets, some tasks end up not being complete or even failing. In this paper, we propose a visibility guaranteed planner by star-convex constrained opti…
Recently, the community has witnessed numerous datasets built for developing and testing state estimators. However, for some applications such as aerial transportation or search-and-rescue, the contact force or other disturbance must be perceived for robust planning and control, which is beyond the…
In this paper, we introduce a complete system for autonomous flight of quadrotors in dynamic environments with onboard sensing. Extended from existing work, we develop an occlusion-aware dynamic perception method based on depth images, which classifies obstacles as dynamic and static. For representi…
In this paper, we propose a novel method to learn face sketch synthesis models by using unpaired data. Our main idea is bridging the photo domain ${\mathcal{X}}$ and the sketch domain Y by using the line-drawing domain ${\mathcal{Z}}$. Specially, we map both photos and sketches to line-drawings by u…
Gradient-based planners are widely used for quadrotor local planning, in which a Euclidean Signed Distance Field (ESDF) is crucial for evaluating gradient magnitude and direction. Nevertheless, computing such a field has much redundancy since the trajectory optimization procedure only covers a very
This paper presents a decentralized and asynchronous systematic solution for multi-robot autonomous navigation in unknown obstacle-rich scenes using merely onboard resources. The planning system is formulated under gradient-based local planning framework, where collision avoidance is achieved by for…
The quadrotor is popularly used in challenging environments due to its superior agility and flexibility. In these scenarios, trajectory planning plays a vital role in generating safe motions to avoid obstacles while ensuring flight smoothness. Although many works on quadrotor planning have been prop…
Adaptive autonomous navigation with no prior knowledge of extraneous disturbance is of great significance for quadrotors in a complex and unknown environment. The mainstream approach that considers external disturbance is to implement disturbance-rejected control and path tracking. However, the robu
The development of aerial autonomy has enabled aerial robots to fly agilely in complex environments. However, dodging fast-moving objects in flight remains a challenge, limiting the further application of unmanned aerial vehicles (UAVs). The bottleneck of solving this problem is the accurate percept…
With the autonomy of aerial robots advances in recent years, autonomous drone racing has drawn increasing attention. In a professional pilot competition, a skilled operator always controls the drone to agilely avoid obstacles in aggressive attitudes, for reaching the destination as fast as possible.
This paper proposes a systematic solution that uses an unmanned aerial vehicle (UAV) to aggressively and safely track an agile target. It properly handles the challenging situations where the intent of the target and the dense environments are unknown. Our work is divided into two parts: target moti…
For quadrotor trajectory planning, describing a polynomial trajectory through coefficients and end-derivatives both enjoy their own convenience in energy minimization. We name them double descriptions of polynomial trajectories. The transformation between them, causing most of the inefficiency and i…
In autonomous navigation, sensors suffer from massive occlusion in cluttered environments, leaving a significant amount of space unknown. In practice, treating the unknown space in optimistic or pessimistic ways both set limitations on planning performance. Therefore, aggressiveness and safety canno…
Maintaining a map online is resource-consuming while a robust navigation system usually needs environment abstraction via a well-fused map. In this paper, we propose a mapless local planner which directly conducts such abstraction on the unfused sensor data. A limited-memory data structure with a re…
In this letter, we propose a lightweight yet effective Topology Guided Kinodynamic planner (TGK-Planner) for quadrotor aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, with novel designs to improve the robustness
Recently, quadrotors are gaining significant attention in aerial transportation and delivery. In these scenarios, an accurate estimation of the external force is as essential as the six degree-of-freedom (DoF) pose since it is of vital importance for planning and control of the vehicle. To this end,…
The visibility of targets determines performance and even success rate of various applications, such as active slam, exploration, and target tracking. Therefore, it is crucial to take the visibility of targets into explicit account in trajectory planning. In this paper, we propose a general metric f…
Multicopters are able to perform high maneuverability yet their potential have not been fully achieved. In this work, we propose a full-body, optimization-based motion planning framework that takes shape and attitude of aerial robot into consideration such that the aggressiveness of drone maneuverin…
With much research has been conducted into trajectory planning for quadrotors, planning with spatial and temporal optimal trajectories in real-time is still challenging. In this letter, we propose a framework for large-scale waypoint-based polynomial trajectory generation, with highlights on its sup
Significant progress has been made with artistic robots. However, existing robots fail to produce high-quality portraits in a short time. In this work, we present a drawing robot, which can automatically transfer a facial picture to a vivid portrait, and then draw it on paper within two minutes aver…
Gradient-based trajectory optimization (GTO) has gained wide popularity for quadrotor trajectory replanning. However, it suffers from local minima, which is not only fatal to safety but also unfavorable for smooth navigation. In this paper, we propose a replanning method based on GTO addressing this…
Euclidean Signed Distance Field (ESDF) is useful for online motion planning of aerial robots since it can easily query the distance and gradient information against obstacles. Fast incrementally built ESDF map is the bottleneck for conducting real-time motion planning. In this paper, we investigate…
In this paper, we investigate the problem of enabling a drone to fly through a tilted narrow gap, without a traditional planning and control pipeline. To this end, we propose an end-to-end policy network, which imitates from the traditional pipeline and is fine-tuned using reinforcement learning. Un…
Facial attractiveness prediction has drawn considerable attention from image processing community. Despite the substantial progress achieved by existing works, various challenges remain. One is the lack of accurate representation for facial composition, which is essential for attractiveness evaluati…
Neural machine translation models usually use the encoder-decoder framework and generate translation from left to right (or right to left) without fully utilizing the target-side global information. A few recent approaches seek to exploit the global information through two-pass decoding, yet have li…
The long-short-term memory (LSTM), though powerful, is memory and computa\x02tion expensive. To alleviate this problem, one approach is to compress its weights by quantization. However, existing quantization methods usually have inferior performance when used on LSTMs. In this paper, we first show t…
In this letter, we propose a novel motion planning framework for quadrotor teach-and-repeat applications. Instead of controlling the drone to precisely follow the teaching path, our method converts an arbitrary jerky human-piloted trajectory to a topologically equivalent one, which is guaranteed to
In this paper, we propose a novel dense surfel mapping system that scales well in different environments with only CPU computation. Using a sparse SLAM system to estimate camera poses, the proposed mapping system can fuse intensity images and depth images into a globally consistent model. The system…
In this letter, we propose a robust and efficient quadrotor motion planning system for fast flight in three-dimensional complex environments. We adopt a kinodynamic path searching method to find a safe, kinodynamic feasible, and minimum-time initial trajectory in the discretized control space. We im
Drones are enabling new forms of cinematography. Aerial filming via drones in action scenes is difficult because it requires users to understand the dynamic scenarios and operate the drone and camera simultaneously. Existing systems allow the user to manually specify the shots and guide the drone to…
In this paper, we propose a framework for online quadrotor motion planning for autonomous navigation in unknown environments. Based on the onboard state estimation and environment perception, we adopt a fast marching-based path searching method to find a path on a velocity field induced by the Eucli…
In this paper, we present a framework to do optimal time allocation for quadrotor trajectory generation. Using this method, we can generate minimum-time piecewise polynomial trajectories for quadrotor flights. We decouple the quadrotor trajectory generation problem into two folds. Firstly we generat…
In this paper, we propose a trajectory generation framework for quadrotor autonomous navigation in unknown 3-D complex environments using gradient information. We decouple the trajectory generation problem as front-end path searching and back-end trajectory refinement. Based on the map that is incre…
In this paper, we present an optimization-based framework for generating quadrotor trajectories which are free of collision in dynamic environments with both static and moving obstacles. Using the finite-horizon motion prediction of moving obstacles, our method is able to generate safe and smooth tr…
In this work, we present a solution to real-time monocular dense mapping. A tightly-coupled visual-inertial localization module is designed to provide metric and high-accuracy odometry. A motion stereo algorithm is proposed to take the video input from one camera to produce local depth measurements…