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Reinforcement Learning-Based Tendon-Driven Bionic Jellyfish Robot Achieves Closed-Loop Depth Control

A tendon-driven bionic jellyfish robot achieves 150° bending through soft actuators that combine a flexible substrate with discrete constraints, with tendon displacement and bending angle approximately linear. Eight actuators driven by four servos enable stable swimming, attitude adjustment, and self-righting. A reinforcement learning controller trained on this linear actuation characteristic achieved closed-loop depth regulation in both simulation and physical experiments.

Part of the event: Tendon-driven jellyfish robot achieves reinforcement-learning-based deep closed-loop control

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