Economic model predictive control for obstacle-aided snake robot locomotion

被引：5
|
作者：
Mueller, Evan [1 ]
Koehler, Philipp N. [1 ]
Pettersen, Kristin Y. [2 ]
Allgoewer, Frank [1 ]
机构：
[1] Univ Stuttgart, Inst Syst Theory & Automat Control, Stuttgart, Germany
[2] Norwegian Univ Sci & Technol, Ctr Autonomous Marine Operat & Syst, Dept Engn Cybernet, Trondheim, Norway
来源：
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词：
Model Predictive Control; Mobile robots; Obstacles; Trajectory planning;
D O I：
10.1016/j.ifacol.2020.12.2622
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper studies the application of economic model predictive control (MPC) to snake robot locomotion. The proposed MPC algorithm integrates the gait pattern creation into the closed loop by maximizing the forward snake velocity. We consider both purely planar locomotion as well as obstacle-aided locomotion. A compliant obstacle-snake contact model is introduced, rendering the interaction dynamics considered in the optimal control problem smooth. We illustrate the efficacy of the scheme by numerical simulations. The emerging gait patterns are undulatory and can make simultaneous use of anisotropic ground friction and obstacles. Copyright (C) 2020 The Authors.
引用
收藏
页码：9702 / 9708
页数：7
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