22 accepted papers
Diffusion models have been promising for trajectory generation tasks due to their ability to capture multimodal behaviors, but their closed-box nature and unconstrained denoising often undermine kinodynamic feasibility. We propose a novel Coupled-Layer Diffusion Model (CLDM) that explicitly embeds a
Current AAV autonomous flights exhibit efficient performance in both indoor and field environments. However, they often face significant challenges in large-scale and cluttered environments, where the vast amount of captured data can lead to computation and storage bottlenecks. Additionally, the existin…
Current UAV autonomous flights exhibit efficient performance in both indoor and field environments. However, they often face significant challenges in large-scale and cluttered environments, where the vast amount of captured data can lead to computation and storage bottlenecks. Additionally, the exi
Indoor disaster relief and rescue missions require quadrotors to fully exploit their maneuverability in real-time. However, the computational complexity induced by the underactuated kinodynamics conflicts with the rapid replanning requirement. For agile trajectory planning in cluttered and unknown e
The multirotor unmanned aerial vehicle (UAV) requires precise control over thrust output when operating in wind-disturbed environments or executing intricate flight missions. Although current commercial force sensors offer high sensitivity and accuracy, they are often heavy and costly. These charact…
This paper studies a novel application of an aerial manipulator (AM)-the contact-based landing on a mobile platform. An AM is inherently unstable, under-actuated, and usually loses some DOFs while contacting environments. Meanwhile, the AM's flight state is susceptible to uncertain movements of the…
Unmanned aerial vehicles (UAVs) must fly at low altitudes to execute certain missions when operating in complex mountainous areas. However, in these environments, UAVs lose their line-of-sight (LOS) communication with the ground station (GS) due to the obstruction of the mountains and are unable to
Building suitable representations for diversified environments to enable robot autonomous navigation is a complicated task, especially for large-scale environments, where the captured vast amount of data will give rise to computation and storage bottlenecks. In this letter, we first propose the rand
The vast amount of data captured by robots in large-scale environments brings the computing and storage bottlenecks to the typical methods of modeling the spaces the robots travel in. In order to efficiently construct a compact terrain model from uncertain, incomplete point cloud data of large-scale…
Generating meaningful spatial models of physical environments is a crucial ability for autonomous navigation of mobile robots. This paper considers the problem of building continuous occupancy maps from sparse and noisy sensor data. To this end, we propose a new method named random mapping maps that…
To address the problem of building accurate and coherent models for large-scale terrains from incomplete and noisy sensor data, this paper proposes a novel framework that can efficiently infer terrain structures by divisionally providing the best linear unbiased estimates for the elevation values. T…
Pedestrian trajectories and actions prediction in complex environment is challenging due to the complexity of human behavior and a variety of internal and external stimuli. Much works has gone towards predicting trajectories and actions separately without mining the coupling relationships between th…
Zero-shot voice conversion (VC) where both source and target speakers are unseen in the training dataset has become a new research direction. Using speaker embeddings instead of one-hot vectors to represent speaker identity is a key point, which makes VC models work on unseen speakers. In our work,…
Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and where specifically. A major challenge in VPR is to handle changes of environmental conditions including weather, season…
The objective of the study is to develop a framework for automatic breast cancer detection with merging four imaging modes. Attempts were made for tumor classification and segmentation; using a multi-parametric Magnetic Resonance Imaging (MRI) method on breast tumors. MRI data of the breast were obt…
Glass curtain walls have been widely used in modern architecture. This makes it urgent to inspect and clean these glasses at regular intervals. Up to now, most of these work is performed by workers, which is expensive and inefficient. Therefore, a novel robot-the contact aerial manipulator system-is…
Contact-based operation in moving process is a challenging problem for aerial manipulators. It requires the whole system to maintain steady contact with external environment, to track some predefined trajectories on surfaces, and simultaneously to present some fixed contact force. Aiming at this pro…
Place recognition and loop closure detection are challenging for long-term visual navigation tasks. SeqSLAM is considered to be one of the most successful approaches to achieve long-term localization under varying environmental conditions and changing viewpoints. SeqSLAM uses a brute-force sequentia…
The dangerous work situation in industrial leakage accidents urgently needs a flexible and small robot to help workers perform operations and to protect them from being injured. An aerial manipulator system consisting of a hexa-rotor UAV and a one-DOF manipulator is developed, and is used to press a…
Grasping a moving target has been investigated extensively for fixed-base manipulator. However, such a task becomes much more challenging when the manipulator is free flying in the air with an UAV. Towards moving target grasping, this paper presents an aerial manipulator system composed of a hex-rot…
Place recognition is one of the major challenges for the LiDAR-based effective localization and mapping task. Traditional methods are usually relying on geometry matching to achieve place recognition, where a global geometry map need to be restored. In this paper, we accomplish the place recognition…
Reliable mapping and hazard detection are prerequisites for autonomous navigation for unmanned ground vehicles. Because of the uncertainty and vibration induced by high-speed navigation and rugged terrain, the problem of mapping for high-speed off-road autonomous navigation has not been completely s…