The USA Engineer Research and Development Center (ERDC) has conducted on-/off-road experimental field testing with full-sized and scale-model military vehicles for more than fifty years. Some 4000 acres of local terrain are available for tailored field evaluations or verification/validation of future robotic designs in a variety of climatic regimes. Field testing and data collection procedures, as well as techniques for quantifying terrain in engineering terms, have been developed and refined into algorithms and models for predicting vehicle-terrain interactions and resulting forces or speeds of military-sized vehicles. Based on recent experiments with Matilda, Talon, and Pacbot, these predictive capabilities appear to be relevant to most robotic systems currently in development. Utilization of current testing capabilities with sensor-based vehicle drivers, or use of the procedures for terrain quantification from sensor data, would immediately apply some fifty years of historical knowledge to the development, refinement, and implementation of future robotic systems. Additionally, translation of sensor-collected terrain data into engineering terms would allow assessment of robotic performance a priori deployment of the actual system and ensure maximum system performance in the theater of operation.
Snowfields are challenging terrain for lightweight (<50 kg) unmanned ground vehicles. Deep sinkage, high snowcompaction
resistance, traction loss while turning and ingestion of snow into the drive train can cause immobility within
a few meters of travel. However, for suitably designed vehicles, deep snow offers a smooth, uniform surface that can
obliterate obstacles. Key requirements for good over-snow mobility are low ground pressure, large clearance relative to
vehicle size and a drive system that tolerates cohesive snow.
A small robot will invariably encounter deep snow relative to its ground clearance. Because a single snowstorm can
easily deposit 30 cm of fresh snow, robots with ground clearance less than about 10 cm must travel over the snow rather
than gain support from the underlying ground. This can be accomplished using low-pressure tracks (< 1.5 kPa). Even
still, snow-compaction resistance can exceed 20% of vehicle weight. Also, despite relatively high traction coefficients
for low track pressures, differential or skid steering is difficult because the outboard track can easily break traction as the
vehicle attempts to turn against the snow. Short track lengths (relative to track separation) or coupled articulated robots
offer steering solutions for deep snow.
This paper presents preliminary guidance to design lightweight robots for good mobility over snow based on mobility
theory and tests of PackBot, Talon and SnoBot, a custom-designed research robot. Because many other considerations
constrain robot designs, this guidance can help with development of winterization kits to improve the over-snow
performance of existing robots.
Conference Committee Involvement (7)
Unmanned Systems Technology XV
1 May 2013 | Baltimore, Maryland, United States
Unmanned Systems Technology XIV
25 April 2012 | Baltimore, Maryland, United States