Obstacle Avoidance in Dynamic Environments via Tunnel-Following MPC with Adaptive Guiding Vector Fields
Paper i proceeding, 2023

This paper proposes a motion control scheme for robots operating in a dynamic environment with concave obstacles. A Model Predictive Controller (MPC) is constructed to drive the robot towards a goal position while ensuring collision avoidance without direct use of obstacle information in the optimization problem. This is achieved by guaranteeing tracking performance of an appropriately designed receding horizon path. The path is computed using a guiding vector field defined in a subspace of the free workspace where each point in the subspace satisfies a criteria for minimum distance to all obstacles. The effectiveness of the control scheme is illustrated by means of simulation.

Författare

Albin Dahlin

Chalmers, Elektroteknik, System- och reglerteknik

Yiannis Karayiannidis

Department of Automatic Control

Lunds universitet

Proceedings of the IEEE Conference on Decision and Control

07431546 (ISSN) 25762370 (eISSN)

Vol. 2023 5784-5789
9798350301243 (ISBN)

62nd IEEE Conference on Decision and Control, CDC 2023
Singapore, Singapore,

Ämneskategorier

Robotteknik och automation

DOI

10.1109/CDC49753.2023.10383988

Mer information

Senast uppdaterat

2024-02-23