ADAPT: Adaptive Dual-projection Architecture for Perceptive Traversal
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Locomotion | Stairs (Simulated) | Traversing Rate95.9 | 11 | |
| Humanoid Locomotion | Simulation Plane | Success Rate (Rsucc)100 | 10 | |
| Humanoid Locomotion | Simulation Jump | Success Rate (Rsucc)98.67 | 5 | |
| Humanoid Locomotion | Simulation Hurdle | Success Rate (Rsucc)90 | 5 | |
| Humanoid Locomotion | Simulation Beam | Success Rate (Rsucc)96.67 | 5 | |
| Humanoid Locomotion | Simulation Pole | Success Rate98 | 5 | |
| Humanoid Locomotion | Simulation Narrow Gate | Success Rate (Rsucc)80 | 5 | |
| Training Efficiency | Simulation | Train Iteration Time (s)11.3 | 4 |