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Walk the PLANC: Physics-Guided RL for Agile Humanoid Locomotion on Constrained Footholds

Description

Bipedal humanoid robots must precisely coordinate balance, timing, and contact decisions when locomoting on constrained footholds such as stepping stones, beams, and planks -- even minor errors can lead to catastrophic failure. Classical optimization and control pipelines handle these constraints well but depend on highly accurate mathematical representations of terrain geometry, making them prone to error when perception is noisy or incomplete. Meanwhile, reinforcement learning has shown strong

Source

http://arxiv.org/abs/2601.06286v1