PEGrad projects energy-minimization gradients orthogonal to task-reward gradients in RL, achieving 64% torque reduction in simulation and reduced battery draw on a Unitree Go2 without sacrificing task reward.
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Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control
PEGrad projects energy-minimization gradients orthogonal to task-reward gradients in RL, achieving 64% torque reduction in simulation and reduced battery draw on a Unitree Go2 without sacrificing task reward.