25 accepted papers
A central challenge in robust quadruped locomotion, which relies solely on proprioceptive information, is how to effectively encode the history of observations. While current methods, such as regression, struggle with high-dimensional multi-time-step histories, and Temporal Convolutional Networks (T…
This paper proposes a Planar-Sector Line-of-Sight (PS-LOS) guidance law and an accompanying control stack for lifting-wing quadcopters, enabling robust image-based interception of agile targets. The PS-LOS relaxes conventional conical constraints, preserving maneuverability while reducing aerodynami…
Ultra-low altitude UAVs (below 120 meters) are gaining importance in the booming low-altitude economy, where GNSS signals are often unreliable or unavailable. Vision-based localization emerges as a promising alternative; however, existing benchmarks are not designed for ultra-low flight and typicall
Safety is a critical requirement in robotics, leading to extensive research in Safe Reinforcement Learning. While most existing methods utilize soft constraints to limit cumulative violations, robotic control scenarios demand that instantaneous safety costs also converge rapidly following a safety e
6D pose estimation is a central problem in robot vision. Compared with pose estimation based on point correspondences or its robust versions, correspondence-free methods are often more flexible. However, existing correspondence-free methods often rely on feature representation alignment or end-to-en
Estimating the six degrees of freedom relative poses is a fundamental problem in robotics. Generally, correspondence-based methods are often vulnerable to mismatches in features between the source and the target. This paper presents an alternative approach: estimating the relative pose globally with
In this paper, we present DL-Clip, an innovative online learning approach for nonlinear stabilizing control that operates without prior knowledge of system dynamics or reward signals, while significantly improving training efficiency. DL-Clip introduces a novel integration of stabilizing control wit
In recent times, Lyapunov theory has been in-corporated into learning-based control methods to provide a stability guarantee. However, merely satisfying the Lyapunov conditions does not fully leverage the capabilities of the Neural Network (NN) controller. Furthermore, training an effective Lyapunov
This letter proposes a fault-tolerant control (FTC) framework for a novel type of aircraft—lifting-wing multicopters. The core of the framework is an attitude controller based on nonlinear model predictive control (NMPC), where the objective function of the NMPC is designed on the based of the relax
Wind disturbance is a critical challenge for uninhabited aerial vehicles (UAVs), particularly for hybrid vertical takeoff and landing (VTOL) UAVs such as lifting-wing quadcopters, which are prone to aerodynamic disturbances like gusts and turbulence due to their wing structure. Existing control stra
Recently, the concept of homotopic trajectory planning has emerged as a novel solution to navigation in large-scale obstacle environments for swarm robotics, offering a wide range of applications. However, it lacks an efficient homotopic path planning method in large-scale obstacle environments. Thi
Learning-based control policies are widely used in various tasks in the field of robotics and control. However, formal (Lyapunov) stability guarantees for learning-based controllers with nonlinear dynamical systems are challenging to obtain. We propose a novel control approach, namely Control with…
As the usage of bi-copters increases in military and civilian fields, the demand for reliable bi-copters is on the rise. This study focuses on controlling a bi-copter under rotor or servo stuck failure. A relaxed hover solution is derived for the bi-copter, by solving an optimization problem subject…
In V-SLAM, the estimation of relative camera pose is crucial to determine the spatial relationship between consecutive camera images, helping to accurately track the movement of the camera in its environment. In small indoor scenes, when the training set is limited, which is very common in robot SLA…
The planning and control of a robot swarm in a complex environment has attracted increasing attention. To this end, the concept of virtual tubes has been taken up in our previous work. Specifically, a variable-width virtual tube is designed to prevent collisions with obstacles in complex environment
Automatic landing of tethered unmanned aerial vehicles (UAVs) is an important issue. Typically, UAVs rely on location sensors such as global navigation satellite system (GNSS) and external cameras to obtain location data. However, harsh environments such as denial GNSS or strong winds make it diffic…
It is often necessary for drones to complete delivery, photography, and rescue in the shortest time to increase efficiency. Many autonomous drone races provide platforms to pursue algorithms to finish races as quickly as possible for the above purpose. Unfortunately, existing methods often fail to k…
It is crucial for hybrid unmanned aerial vehicles, such as lifting-wing multicopters, to plan a continuous, smooth, and collision-free trajectory to avoid obstacles. Unlike quad-copters, which typically work in indoor environments, lifting-wing multicopters typically fly at a high altitude with a hi…
Searching in a denied environment is challenging for swarm robots as no assistance from GNSS, mapping, data sharing, and central processing is allowed. However, using olfactory and auditory signals to cooperate like animals could be an important way to improve the collaboration of swarm robots. In t…
Swarm robotics plays a non-negligible role in actual practice because of its scalability and robustness. Besides some specific studies, there is still a lack of overall approaches to solving the search and rescue problem in a communication-denied environment. This paper presents a bee-inspired swarm…
This paper proposes a model of a class of regular virtual tubes that can generate safe, feasible, and smooth space for a robotics swarm in an obstacle-dense environment, especially for a drone swarm based on the flocking model. The regular principles are first proposed, and the regular conditions ar…
The success of deep learning methods relies on the availability of well-labeled large-scale datasets. However, for medical images, annotating such abundant training data often requires experienced radiologists and consumes their limited time. Few-shot learning is developed to alleviate this burden,…
This paper aims to present a drone swarm light show design platform to support STEAM (science, technology, engineering, art and mathematics) education for K-12 children. With this platform, children can use this platform to design a drone swarm light show easily. To this end, the architecture of thi…
For most people on the ground, facing an unwanted drone buzzing around overhead, there is not a lot that we can do, especially if it is out of gun (radio wave gun or shotgun) range. A solution to this is to use intercept drones that seek out and bring down other drones. In order to make the intercep…
Relative pose estimation is critical for collaborative multi-agent systems. To achieve accurate and low-cost localization in cluttered and GPS-denied environments, we propose a novel relative pose estimation system based on a designed active infrared coded target. Specifically, each agent is equippe…