Optimal Path Following Control With Efficient Computation for Snake Robots Subject to Multiple Constraints and Unknown Frictions

• Published in: IEEE robotics and automation letters Vol. 7; no. 4; pp. 9151 - 9158
• Main Authors: Li, Xiaohan, Ren, Chao, Ma, Shugen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Biologically-inspired robots; Computational modeling; Constraint modelling; Double integrators; Dynamic models; Environment models; Friction; motion control; Optimization; Predictive control; Predictive models; Real-time systems; Robots; Robust control; Sideslip; Snake robots; State observers; Trajectory planning
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2022.3190642

This letter proposes a real-time optimal robust path following control scheme for planar snake robots without sideslip constraints using model predictive control (MPC). One of the features is that a linear double-integrator model rather than the complex dynamic model of snake robots is used for the MPC design to improve calculation efficiency. Moreover, in addition to constraints on joint angles, velocity, and acceleration for security, constraints on the joint offset and velocity are also considered to keep the snake robot moving forward efficiently. And the multiple inequality constraints are handled by a novel constraints translator. Furthermore, to achieve robust path following control subject to unknown and varied friction forces and disturbances, two reduced-order structure-improved extended state observers are designed to avoid complex environmental modeling. Extensive comparative experiments were conducted to verify the constraints design and the effectiveness of the proposed control scheme.