Details

Autor(en) / Beteiligte

• Terry Suh, H. J.
• Xiong, Xiaobin
• Singletary, Andrew
• Ames, Aaron D.
• Burdick, Joel W.

Titel

Energy-Efficient Motion Planning for Multi-Modal Hybrid Locomotion

Ist Teil von

• 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, p.7027-7033

Ort / Verlag

IEEE

Erscheinungsjahr

2020

Link zum Volltext

• Volltext

Quelle

IEEE Xplore Digital Library

Beschreibungen/Notizen

• Hybrid locomotion, which combines multiple modalities of locomotion within a single robot, enables robots to carry out complex tasks in diverse environments. This paper presents a novel method for planning multi-modal locomotion trajectories using approximate dynamic programming. We formulate this problem as a shortest-path search through a state-space graph, where the edge cost is assigned as optimal transport cost along each segment. This cost is approximated from batches of offline trajectory optimizations, which allows the complex effects of vehicle under-actuation and dynamic constraints to be approximately captured in a tractable way. Our method is illustrated on a hybrid double-integrator, an amphibious robot, and a flying-driving drone, showing the practicality of the approach.