Obstacle Avoidance in Dynamic Environments via Tunnel-Following MPC with Adaptive Guiding Vector Fields
- Resource Type
- Conference
- Authors
- Dahlin, Albin; Karayiannidis, Yiannis
- Source
- 2023 62nd IEEE Conference on Decision and Control (CDC) Decision and Control (CDC), 2023 62nd IEEE Conference on. :5784-5789 Dec, 2023
- Subject
- Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Tracking
Dynamics
Green products
Stars
Predictive models
Trajectory
Collision avoidance
- Language
- ISSN
- 2576-2370
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.