Home /Research /Energy-efficient and damage-recovery slithering gait design for a snake-like robot based on reinforcement learning and inverse reinforcement learning
LOCOMOTION

Energy-efficient and damage-recovery slithering gait design for a snake-like robot based on reinforcement learning and inverse reinforcement learning

Zhenshan Bing, Christian Lemke, Long Cheng, K. X. Huang, Alois Knoll

Year
2020
Citations
55
Access
Open access

Keywords

Reinforcement learningComputer scienceController (irrigation)RobotFlexibility (engineering)Artificial intelligenceGaitParameterized complexityEnergy (signal processing)Control theory (sociology)

Related papers

Browse all LOCOMOTION papers