A morphing five-bar linkage leg lets robots adapt between height-advantaged walking and force-advantaged rescue tasks.
Real-world embodied ai through a morphologically adaptive quadruped robot
2 Pith papers cite this work. Polarity classification is still indexing.
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A reinforcement learning method lets legged robots jointly learn information-seeking actions and predict joint-level and global embodiment parameters using a history-augmented URMA model in simulation.
citing papers explorer
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Dynamically Extensible and Retractable Robotic Leg Linkages for Multi-task Execution in Search and Rescue Scenarios
A morphing five-bar linkage leg lets robots adapt between height-advantaged walking and force-advantaged rescue tasks.
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Active Embodiment Identification with Reinforcement Learning for Legged Robots
A reinforcement learning method lets legged robots jointly learn information-seeking actions and predict joint-level and global embodiment parameters using a history-augmented URMA model in simulation.