DRIVE Through the Unpredictability:From a Protocol Investigating Slip to a Metric Estimating Command Uncertainty

TL;DR

This paper introduces the DRIVE protocol for standardized data collection to characterize slip in off-road autonomous navigation, proposing a new metric to estimate command uncertainty and assess deployment risks.

Contribution

It presents a novel protocol for system identification of slip behavior and introduces an unpredictability metric to evaluate command uncertainty in off-road UGVs.

Findings

Validated the DRIVE protocol on diverse terrains and platforms

Established the relationship between command velocity and slip behavior

Proposed an uncertainty metric for risk assessment

Abstract

Off-road autonomous navigation is a challenging task as it is mainly dependent on the accuracy of the motion model. Motion model performances are limited by their ability to predict the interaction between the terrain and the UGV, which an onboard sensor can not directly measure. In this work, we propose using the DRIVE protocol to standardize the collection of data for system identification and characterization of the slip state space. We validated this protocol by acquiring a dataset with two platforms (from 75 kg to 470 kg) on six terrains (i.e., asphalt, grass, gravel, ice, mud, sand) for a total of 4.9 hours and 14.7 km. Using this data, we evaluate the DRIVE protocol's ability to explore the velocity command space and identify the reachable velocities for terrain-robot interactions. We investigated the transfer function between the command velocity space and the resulting steady-state slip for an SSMR. An unpredictability metric is proposed to estimate command uncertainty and help assess risk likelihood and severity in deployment. Finally, we share our lessons learned on running system identification on large UGV to help the community.