12 accepted papers
This letter presents a saturation-triggered adaptive fault-tolerant control framework for underwater vehicles to handle concurrent thruster failures and environmental disturbances. Unlike existing methods that suffer from performance degradation when disturbances exceed predefined bounds, this paper
Underwater vehicles face control challenges including hydrodynamic parameter uncertainties and environmental disturbances. While Koopman-based model predictive control (Koopman-MPC) offers computational efficiency through linear lifted representations, existing methods rely on offline-collected data
This paper investigates the control problem of underwater vehicles subject to time-varying external disturbances and actuator faults. A novel passive fault-tolerant control (PFTC) scheme is developed to address the coupled disturbance-fault dynamics inherent in underwater vehicle systems. The propos
Semantic Scene Completion (SSC) aims to reconstruct the entire 3D scene in terms of both occupancy and semantics, serving as a fundamental task for autonomous driving and robotic systems. Camera-based methods have seen significant advancements due to their low cost and rich visual cues. However, pre
Air-ground robots have received more and more attention and applications due to their air-to-ground motion performance and excellent energy efficiency. However, airground robots have many gaps including complex structure mechanisms, low terrain adaptability and low-precision controllers to significa
Mainstream visual-inertial SLAM systems use point features for motion estimation and localization. However, point features do not perform well in scenes such as weak texture and motion blur. Therefore, the introduction of line features has received a lot of attention. In this letter, we propose a po
Navigating robots through dynamic multi-robot environments, avoiding collisions with both other robots and obstacles, has emerged as a central challenge in robotics. The existing approaches fall short in allowing the policy network to effectively capture spatial-temporal reciprocal collision avoidan…
For aerial swarms, formation flight has been applied in various scenes. However, most existing works do not consider balancing the conflicting requirements among keeping formation, keeping the smoothness of trajectories, and obstacle avoidance within the limited time. To address this issue, we propo…
Generalizing visual reinforcement learning is fundamental to robot visual navigation, involving the acquisition of a policy from interactions with source environments to facilitate adaptation to analogous, yet unfamiliar target environments. Recent advancements capitalize on data augmentation techni…
Highly accurate and efficient map in unknown and complex environments is essential for robotics navigation. Traditionally, mobile robot platforms are often computationally constrained when using multiple sensors to process large amounts of input data. In previous works, some of them have been deploy…
This letter reports a general path following framework for the tractor-trailers system in Global Positioning System (GPS)-denied environments. Compared to existing methods, this approach prioritizes a robust, cost-optimized, and easy-to-implement solution. First, to achieve accurate path following,
Most existing trajectory tracking controllers are based on non-skidding and non-slipping assumptions, also assume that full states are accessible, which is unrealistic for real-world applications due to tire-road interaction. This paper presents a novel vision-based approach to achieve high performa…