Vol. 1, No. 3 (September 2026) — Article KAGG:2609.00008

Local Planning under Asymmetric Collision Geometries Across Embodiments

Authors: Anika Roth, Selin Aydin, Lukas Brandt

Robot Learning Lab, University of Zurich, Zurich, Switzerland

[Received 2026-09-08; accepted 2026-09-19; published online 2026-09-22]

Abstract:

Local planners that run across quadrupeds, wheeled robots, and humanoids commonly represent every body by a symmetrically inflated disk or a static footprint, discarding the swing envelope of the legs, humanoid headroom, and the directional structure of clearance. This paper builds an embodiment-accurate collision layer on the AgniNav configuration-driven backbone. The layer replaces the static envelope with a configuration-dependent collision set, formed by the footprint and a phase-indexed leg-swing volume for quadrupeds, a body envelope for wheeled rovers, and a full-body capsule with arm reach and a headroom term for humanoids, and it scores candidate trajectories with a clearance cost that is anisotropic in each body frame. The planner is evaluated in 15 Isaac Lab mixed-embodiment scenes with diagonal gaps of 45 to 75 degrees, cluttered corridors, and multi-robot proximity, across four embodiments, five seeds, and 30 episodes each. Relative to symmetric inflation, the method raises the feasible passage width gain from 14.2 to 14.8 percent, lowers the collision rate from 0.19 to 0.18 per km, and lowers the 95th-percentile planner runtime from 6.9 to 6.4 ms, while the aggregate spurious-stoppage rate is unchanged at 0.3 per episode. The aggregate gains are modest and concentrate in specific situations: in a 60 degree, 71 cm diagonal gap where the symmetric-inflation quadruped fails 12 of 30 attempts, the swing-aware quadruped passes at 1.2 m/s with 8 cm clearance, and in one corridor the full-body humanoid model reduces spurious stoppages near a wheeled robot from 3.1 to 0.4 per episode.


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Cite this article Anika Roth, Selin Aydin, Lukas Brandt, "Local Planning under Asymmetric Collision Geometries Across Embodiments," Transactions on Intelligent Robotics and Autonomous Systems, 2026, vol. 1, no. 3, KAGG:2609.00008. DOI: 10.5803/kagg.2609.00008.