Abstract
We investigate tracking tasks for an automatic mobile robot with obstacle avoidance. To this end we apply a linear model-predictive control (LMPC) method to the nonlinear robot model. The LMPC uses a linearized robot model around the reference track and takes into account (fixed or moving) obstacles, which the robot has to avoid. The resulting discretized linear-quadratic optimal control problems are solved numerically by a semismooth Newton method, which turns out to be fast and robust. Furthermore, we propose a structure exploitation strategy to reduce the computational effort of the semismooth Newton method. Simulation results for a two-wheeled robot are presented to validate the control algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
