AI & ML
Adaptive stabilization of a leaderless bearing-constrained formation with disturbances
arXiv cs.MA0 views
arXiv:2609.06355v2 Announce Type: replace Abstract: In this paper, we consider the problem of regulating and maintaining a target formation characterized by a set of bidirectional bearing constraints under disturbances. The agents in the formation are modeled by single integrators with deterministic bounded continuous disturbances of which both actual function and upper bound are unavailable for the control design. Due to the time-varying disturbances, the target formation is time-varying. We propose displacement/bearing-only based adaptive sliding mode control laws to uniformly asymptotically stabilize the time-varying target formation and reject the matched disturbances, and provide sufficient conditions to prevent possible collisions. A time-dependent adaptive design method is provided to convert the displacement-based control law to a bearing-only one. In addition, to alleviate chattering phenomena from sliding mode control, smooth adaptive control laws are introduced to guarantee uniform global boundedness of the desired formation. Finally, simulation results are given to support the analysis.
Source:https://arxiv.org/abs/2609.06355PreviousTowards using Large Language Models for Risk Negotiation and Consensus-building in One Health contextsNextAGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games
Related posts
How Many Demonstrations Does a VLA Need? On the Sample Efficiency of VLA Finetuning
0arXiv cs.RO
Altitude-Adaptive UAV-to-Map Image Matching for Aerial Geo-Localization
0arXiv cs.RO
OASIS: Optimization-Aware Subgoal Inference with Safety Constraints for Autonomous Mobile Robot Navigation
0arXiv cs.RO
Fade to... Red? Scheduling Coloured Noise Exploration Supports Efficient Robot Learning with Reduced Movement Jerk
0arXiv cs.RO
DexForesight: Grounding Dexterous Policies with Implicit Spatial Foresight
0arXiv cs.RO
Control-Aware Command Generation for Asynchronous Control and Action Inference with Vision-Based Policies towards Fast Execution
0arXiv cs.RO