VCTP: Vehicle-Conditioned Terrain Planning for Off-Road Navigation

📅 2026-09-15
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🤖 AI Summary
研究解决了越野导航中车辆姿态对行驶表面及车身倾斜的影响问题,通过VCTP方法评估不同方向下的地形,并结合D* Lite算法规划最优路径。
📝 Abstract
A vehicle's heading affects both the surfaces beneath its tires and its pitch and roll. We present Vehicle-Conditioned Terrain Planning (VCTP), which retains these relationships by evaluating shared elevation and surface-ID layers at eight headings. Body geometry constrains admissibility, while loaded wheel contacts determine modeled surface cost and predicted pitch and roll. Established D* Lite and vehicle-state search use these evaluations to plan routes with forward and reverse motion. When observations change, VCTP recomputes every affected body or contact query. In fully observed two-track simulations, sampling at wheel contacts rather than at the vehicle center lowers modeled surface cost by 39.3% while shortening the route. In offline planning on RGator recordings, VCTP also reduces modeled costs over identified surfaces and observed support relative to distance-focused planning, although incomplete coverage leaves full-route rankings unresolved. Selective updates match full recomputation in all 474 comparisons using recorded map changes. These results identify when wheel-contact placement and vehicle heading affect route choice.
Problem

Research questions and friction points this paper is trying to address.

Vehicle-Conditioned Terrain Planning
Off-Road Navigation
Vehicle Heading
Innovation

Methods, ideas, or system contributions that make the work stand out.

Vehicle-Conditioned Terrain Planning
D* Lite
wheel contacts
surface cost
heading
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Akshay Naik
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