An NMPC Approach using Convex Inner Approximations for Online Motion Planning with Guaranteed Collision Avoidance
Tobias Schoels,Luigi Palmieri,Kai O. Arras,Moritz Diehl,Tobias Schoels,Luigi Palmieri,Kai O. Arras,Moritz Diehl
Even though mobile robots have been around for decades, trajectory optimization and continuous time collision avoidance remain subject of active research. Existing methods trade off between path quality, computational complexity, and kinodynamic feasibility. This work approaches the problem using a nonlinear model predictive control (NMPC) framework, that is based on a novel convex inner approxima...
