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.
Go2 developer documentation, 2024
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
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.