Continuous Jumping for Legged Robots on Stepping Stones via Trajectory Optimization and Model Predictive Control

Performing highly agile dynamic motions, such as jumping or running on uneven stepping stones has remained a challenging problem in legged robot locomotion. This paper presents a framework that combines trajectory optimization and model predictive control to perform robust and consecutive jumping on...

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Vydané v:Proceedings of the IEEE Conference on Decision & Control s. 93 - 99
Hlavní autori: Nguyen, Chuong, Bao, Lingfan, Nguyen, Quan
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 06.12.2022
Predmet:
Adaptive control
Dynamics
Legged locomotion
Perturbation methods
Real-time systems
Robots
Uncertainty
ISSN:2576-2370
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Shrnutí:Performing highly agile dynamic motions, such as jumping or running on uneven stepping stones has remained a challenging problem in legged robot locomotion. This paper presents a framework that combines trajectory optimization and model predictive control to perform robust and consecutive jumping on stepping stones. In our approach, we first utilize trajectory optimization based on full-nonlinear dynamics of the robot to generate periodic jumping trajectories for various jumping distances. A jumping controller based on a model predictive control is then designed for realizing smooth jumping transitions, enabling the robot to achieve continuous jumps on stepping stones. Thanks to the incorporation of MPC as a real-time feedback controller, the proposed framework is also validated to be robust to uneven platforms with unknown height perturbations and model uncertainty on the robot dynamics.
ISSN:2576-2370
DOI:10.1109/CDC51059.2022.9993259