Autonomous navigation with convergence guarantees in complex dynamic environments
Year: 2024
Type: article
Abstract: This article addresses the obstacle avoidance problem for setpoint stabilization tasks in complex dynamic 2-D environments that go beyond conventional scenes with isolated convex obstacles. A combined motion planner and controller is proposed that integrates the favorable convergence characteristics of closed-form motion planning techniques with the intuitive representation of system constraints through Model Predictive Control (MPC). The method is analytically proven to accomplish collision avoidance and convergence under soft conditions. Simulation scenarios using a non-holonomic unicycle robot is provided to showcase the efficacy of the control scheme.
Source: Automatica
Authors: Albin Dahlin, Yiannis Karayiannidis
Institutions: Chalmers University of Technology, Lund University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,610
OpenAlex ID: W4405419219