Safety Monitor for Off-Road Planning with Uncertainty Bounded Bekker Costs

TL;DR

This paper introduces a safety monitor for off-road autonomous vehicles that uses a Bekker-based cost model with bounded uncertainty to ensure safety and predictability on uncertain soil conditions, enabling safe operation with minimal intervention.

Contribution

It presents a novel runtime safety monitor that collaborates with any planner, using a bounded uncertainty soil model to enforce safety limits and switch to fallback behaviors.

Findings

The monitor effectively reduces safety violations in simulation across various soil types.

Intervention rates and path efficiency are balanced through tunable safety parameters.

Initial empirical validation confirms the model's practical applicability.

Abstract

Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance safety monitor that collaborates with any planner and uses a Bekker-based cost model with bounded uncertainty. The monitor builds an upper confidence traversal cost from a lightweight pressure sinkage model identified in field tests and checks each planned motion against two limits: maximum sinkage and rollover margin. If the risk of crossing either limit is too high, the monitor switches to a certified fallback that reduces vehicle speed, increases standoff from soft ground, or stops on firmer soil. This separation lets the planner focus on efficiency while the monitor keeps the vehicle within clear safety limits on board. Wheel geometry, wheel load estimate, and a soil raster serve as inputs, which tie safety directly to vehicle design and let the monitor set clear limits on speed, curvature, and stopping at run time. The method carries uncertainty analytically into the upper confidence cost and applies simple intervention rules. Tuning of the sinkage limit, rollover margin, and risk window trades efficiency for caution while keeping the monitor light enough for embedded processors. Results from a simulation environment spanning loam to sand include intervention rates, violation probability, and path efficiency relative to the nominal plan, and a benchtop static loading check provides initial empirical validation.