12 accepted papers
In many real-world scenarios, agents operate across heterogeneous environments where the underlying dynamics and data-generating processes vary. Standard reinforcement learning and imitation learning methods often fail in such settings as they typically assume stationarity and learn policies that ov
In this letter, we propose a safety-critical compliant control strategy designed to strictly enforce interaction force constraints during the physical interaction of robots with environments. The interaction force constraint is interpreted as a new force-constrained control barrier function (FC-CBF)
We propose PRED-MPPI, the first MPPI variant that seamlessly integrates real-time disturbance preview and adaptive discretization for quadrotor tracking control under significant model inaccuracies and time-varying disturbances. Unlike prior MPPI variants (e.g., mathcal{L}_1-MPPI, DA-MPPI), which as…
The coordinated motion of the trolley and hoisting rope improves crane flexibility but poses challenges in precise trajectory conversion and tracking due to disturbances and inaccessible low-level controllers. This letter proposes a disturbance-aware high-precision trajectory planning method integra
SP-based synthesis yields two-time-scale control that allows compliant-joint robots to achieve high-quality tracking at low implementation cost. Composite learning enables exact online identification and control of robots without the stringent condition known as persistent excitation (PE). However, …
Model Predictive Path Integral (MPPI) controllers are drawing increasing attention for their ability to efficiently handle complex systems by leveraging GPU acceleration while with flexible prediction models and cost functions. However, their performance generally degrades with low-quality predictio
Unmanned Aerial Vehicles (UAVs) are gaining attention for inspections due to their improved safety, efficiency, and accuracy, alongside reduced costs and environmental risks. Visual servoing is crucial for autonomous UAV flight in GPS-degraded environments, guiding the UAV by minimizing errors betwe
A flexible active safety motion (FASM) control approach is proposed for collision avoidance in robot manipulators. The key feature is the use of control barrier functions (CBFs) to design flexible CBF-guided safety criteria (CBFSC) with dynamically optimized decay rates, providing both flexibility a
Accurate modeling of dynamic systems is essential for robotics, enhancing system perception and control performance. This work tackles causal modeling challenges for mobile robots under complex uncertainties, including internal model inaccuracies and external environmental disturbances. Unlike first
Neural ODEs (NODEs) are continuous-time neural networks (NNs) that can process data without the limitation of time intervals. They have advantages in learning and understanding the evolution of complex real dynamics. Many previous works have focused on NODEs in concise forms, while numerous physical…
Recent years have witnessed great progress in person re-identification (re-id). Several academic benchmarks such as Market1501, CUHK03 and DukeMTMC play important roles to promote the re-id research. To our best knowledge, all the existing benchmarks assume the same person will have the same clothes…
Person re-identification is an important topic in intelligent surveillance and computer vision. It aims to accurately measure visual similarities between person images for determining whether two images correspond to the same person. State-of-the-art methods mainly utilize deep learning based approa…