Hybrid Feedback Control Design for Non-Convex Obstacle Avoidance

Fuente: arXiv
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Main Authors: Sawant, Mayur, Polushin, Ilia, Tayebi, Abdelhamid
Format: Preprint
Published: 2023
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author Sawant, Mayur
Polushin, Ilia
Tayebi, Abdelhamid
author_facet Sawant, Mayur
Polushin, Ilia
Tayebi, Abdelhamid
contents We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments containing obstacles, with arbitrary non-convex shapes, which can be in close proximity with each other, as long as there exists at least one safe path connecting the initial and the target location. An instrumental transformation that modifies (virtually) the non-convex obstacles, in a non-conservative manner, is introduced to facilitate the design of the obstacle-avoidance strategy. The proposed navigation approach relies on a hybrid feedback that guarantees global asymptotic stabilization of a target location while ensuring the forward invariance of the modified obstacle-free workspace. The proposed hybrid feedback controller guarantees Zeno-free switching between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the modified obstacle-occupied workspace. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness via some numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2304_10598
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Hybrid Feedback Control Design for Non-Convex Obstacle Avoidance
Sawant, Mayur
Polushin, Ilia
Tayebi, Abdelhamid
Robotics
Systems and Control
We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments containing obstacles, with arbitrary non-convex shapes, which can be in close proximity with each other, as long as there exists at least one safe path connecting the initial and the target location. An instrumental transformation that modifies (virtually) the non-convex obstacles, in a non-conservative manner, is introduced to facilitate the design of the obstacle-avoidance strategy. The proposed navigation approach relies on a hybrid feedback that guarantees global asymptotic stabilization of a target location while ensuring the forward invariance of the modified obstacle-free workspace. The proposed hybrid feedback controller guarantees Zeno-free switching between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the modified obstacle-occupied workspace. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness via some numerical simulations.
title Hybrid Feedback Control Design for Non-Convex Obstacle Avoidance
topic Robotics
Systems and Control
url https://arxiv.org/abs/2304.10598