Trafficability Assessment of Deformable Terrain through Hybrid Wheel-Leg Sinkage Detection

Comin, F.J., Lewinger, W.A., Saaj, C. and Matthews, M.C. (2017) Trafficability Assessment of Deformable Terrain through Hybrid Wheel-Leg Sinkage Detection. Journal of Field Robotics, 34 (3). pp. 451-476. ISSN 1556-4959

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Off‐road ground mobile robots are widely used in diverse applications, both in terrestrial and planetary environments. They provide an efficient alternative, with lower risk and cost, to explore or to transport materials through hazardous or challenging terrain. However, nongeometric hazards that cannot be detected remotely pose a serious threat to the mobility of such robots. A prominent example of the negative effects these hazards can have is found on planetary rover exploration missions. They can cause a serious degradation of mission performance at best and complete immobilization and mission failure at worst. To tackle this issue, the work presented in this paper investigates the novel application of an existing enhanced‐mobility locomotion concept, a hybrid wheel‐leg equipped by a lightweight micro‐rover, for in situ characterization of deformable terrain and online detection of nongeometric hazards. This is achieved by combining an improved vision‐based approach and a new ranging‐based approach to wheel‐leg sinkage detection. In addition, the paper proposes an empirical model, and a parametric generalization, to predict terrain trafficability based on wheel‐leg sinkage and a well‐established semiempirical terramechanics model. The robustness and accuracy of the sinkage detection methods implemented are tested in a variety of conditions, both in the laboratory and in the field, using a single wheel‐leg test bed. The sinkage‐trafficability model is developed based on experimental data using this test bed and then validated onboard a fully mobile robot through experimentation on a range of dry frictional soils that covers a wide spectrum of macroscopic physical characteristics.

Additional Information:cited By 3
Divisions:College of Science > School of Engineering
ID Code:37428
Deposited On:07 Oct 2019 10:05

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