Corpus ID: 202661104

An NMPC Approach using Convex Inner Approximations for Online Motion Planning with Guaranteed Collision Freedom

@article{Schoels2019AnNA,
  title={An NMPC Approach using Convex Inner Approximations for Online Motion Planning with Guaranteed Collision Freedom},
  author={Tobias Schoels and Luigi Palmieri and Kai Oliver Arras and Moritz Diehl},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.08267}
}
  • Tobias Schoels, Luigi Palmieri, +1 author Moritz Diehl
  • Published in ArXiv 2019
  • Engineering, Computer Science, Mathematics
  • Even though mobile robots have been around for decades, trajectory optimization and continuous time collision avoidance remains subject of active research. Existing methods trade off between path quality, computational complexity, and kinodynamic feasibility. This work approaches the problem using a model predictive control (MPC) framework, that is based on a novel convex inner approximation of the collision avoidance constraint. The proposed Convex Inner ApprOximation (CIAO) method finds a… CONTINUE READING

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