TY - JOUR
T1 - Guaranteed Collision Avoidance for Autonomous Systems with Acceleration Constraints and Sensing Uncertainties
AU - Rodríguez-Seda, Erick J.
AU - Stipanović, Dušan M.
AU - Spong, Mark W.
N1 - Funding Information:
This work was partially supported by The Boeing Company via the Information Trust Institute, University of Illinois at Urbana–Champaign, and by NSF Grant ECCS-0725433.
Publisher Copyright:
© 2015, The authors.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - A set of cooperative and noncooperative collision avoidance strategies for a pair of interacting agents with acceleration constraints, bounded sensing uncertainties, and limited sensing ranges is presented. We explicitly consider the case in which position information from the other agent is unreliable, and develop bounded control inputs using Lyapunov-based analysis, that guarantee collision-free trajectories for both agents. The proposed avoidance control strategies can be appended to any other stable control law (i.e., main control objective) and are active only when the agents are close to each other. As an application, we study in detail the synthesis of the avoidance strategies with a set-point stabilization control law and prove that the agents converge to the desired configurations while avoiding collisions and deadlocks (i.e., unwanted local minima). Simulation results are presented to validate the proposed control formulation.
AB - A set of cooperative and noncooperative collision avoidance strategies for a pair of interacting agents with acceleration constraints, bounded sensing uncertainties, and limited sensing ranges is presented. We explicitly consider the case in which position information from the other agent is unreliable, and develop bounded control inputs using Lyapunov-based analysis, that guarantee collision-free trajectories for both agents. The proposed avoidance control strategies can be appended to any other stable control law (i.e., main control objective) and are active only when the agents are close to each other. As an application, we study in detail the synthesis of the avoidance strategies with a set-point stabilization control law and prove that the agents converge to the desired configurations while avoiding collisions and deadlocks (i.e., unwanted local minima). Simulation results are presented to validate the proposed control formulation.
KW - Avoidance control
KW - Bounded control
KW - Two-agent systems
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U2 - 10.1007/s10957-015-0824-7
DO - 10.1007/s10957-015-0824-7
M3 - Article
AN - SCOPUS:84959081665
VL - 168
SP - 1014
EP - 1038
JO - Journal of Optimization Theory and Applications
JF - Journal of Optimization Theory and Applications
SN - 0022-3239
IS - 3
ER -