NMPC Strategy for Safe Robot Navigation in Unknown Environments using Polynomial Zonotopes
2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC(2023)
摘要
This work proposes a nonlinear model predictive control (NMPC) strategy for robot navigation in cluttered unknown environments using polynomial zonotopes. The information provided by a laser sensor is used in the computation of the collision-free area. The procedure splits the area into convex subregions which are converted into polynomial zonotopes (PZs) to generate constraints for the NMPC optimal control problem. The PZ is a set representation that can describe polytopes using fewer constraints than conventional half-space representations, thus being more efficient while maintaining the accuracy equivalent to the polytopic case. Numerical experiments demonstrate the advantages of the proposed strategy.
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