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ADAPT: Adaptive Dual-projection Architecture for Perceptive Traversal

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Agile humanoid locomotion in complex 3D en- vironments requires balancing perceptual fidelity with com- putational efficiency, yet existing methods typically rely on rigid sensing configurations. We propose ADAPT (Adaptive dual-projection architecture for perceptive traversal), which represents the environment using a horizontal elevation map for terrain geometry and a vertical distance map for traversable- space constraints. ADAPT further treats its spatial sensing range as a learnable action, enabling the policy to expand its perceptual horizon during fast motion and contract it in cluttered scenes for finer local resolution. Compared with voxel-based baselines, ADAPT drastically reduces observation dimensionality and computational overhead while substantially accelerating training. Experimentally, it achieves successful zero-shot transfer to a Unitree G1 Humanoid and signifi- cantly outperforms fixed-range baselines, yielding highly robust traversal across diverse 3D environtmental challenges.

Shuo Shao, Tianchen Huang, Wei Gao, Shiwu Zhang• 2026

Related benchmarks

TaskDatasetResultRank
LocomotionStairs (Simulated)
Traversing Rate95.9
11
Humanoid LocomotionSimulation Plane
Success Rate (Rsucc)100
10
Humanoid LocomotionSimulation Jump
Success Rate (Rsucc)98.67
5
Humanoid LocomotionSimulation Hurdle
Success Rate (Rsucc)90
5
Humanoid LocomotionSimulation Beam
Success Rate (Rsucc)96.67
5
Humanoid LocomotionSimulation Pole
Success Rate98
5
Humanoid LocomotionSimulation Narrow Gate
Success Rate (Rsucc)80
5
Training EfficiencySimulation
Train Iteration Time (s)11.3
4
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