Journal
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
Volume 78, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2022.102382
Keywords
Quadruped robot; Soft actuators; Tendon-driven motion; Reinforcement learning; Robot gait; Motion control
Funding
- Swedish Research Council (Vetenskapsradet) [2017-04550, 2019-05232]
- Swedish Research Council [2019-05232, 2017-04550] Funding Source: Swedish Research Council
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This paper proposes a new design for quadruped robots using soft actuators driven by tendons as the four legs. The advantages of the proposed soft quadruped robot are inherent safety, less weight, and simpler mechanism, but the challenge lies in deriving the accurate mathematical model for control design. The paper makes contributions in modeling the flexible components, optimizing gaits using soft actor-critic methods, and implementing the learned gaits in a real robot.
Quadruped robots have the advantages of traversing complex terrains that are difficult for wheeled robots. Most of the reported quadruped robots are built by rigid parts. This paper proposes a new design of quadruped robots using soft actuators driven by tendons as the four legs. Compared to the rigid robots, the proposed soft quadruped robot has inherent safety, less weight and simpler mechanism for fabrication and control, but the corresponding challenge is that the accurate mathematical model applicable to model-based control design of the soft robot is difficult to derive by dynamics. To synthesize the optimal gait controller of the soft-legged robot, the paper makes the following contributions. First, the flexible components of the quadruped robot are modeled with different finite element and lumped parameter methods. The model accuracy and computation efficiency are analyzed. Second, soft actor-critic methods and curriculum learning are applied to learn the optimal gaits for different walking tasks. Third, The learned gaits are implemented in an in-house robot to transport hand tools. Preliminary results show that the robot can walk forward and correct the walking directions.
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