The passing of a wheeled or tracked vehicle over soft or deformable soil creates ruts. The depth of these ruts is proportional to the weight of the vehicle and the soil trafficability; the ability of the soil to support traffic from vehicles. Assessing soil trafficability is often a manual and labor-intensive process. We evaluate the ability of lidar and depth cameras to detect changes in rut depth with the goal of minimizing manual or automated evaluation via soil strength testing. Our sensor-based approach mimics the process used by human operators when measuring rut depth. We compare this approach with machine-centered approaches with the goal of improving correlation between soil strength measurements and rut depth. In general, we find that all sensors are able to measure rut depth within the uncertainty bounds of soil and rut depth models for light vehicles.
KEYWORDS: Muons, Monte Carlo methods, Sensors, Sensing systems, Optimization (mathematics), Environmental sensing, Defense and security, Clouds, Systems modeling, Robotics
We present an overview of MUONS: the Michigan tech Unstructured and Off-road Navigation Stack. MUONS is a ROS-based point-cloud-based navigation stack designed to enable traversal of complex terrain that may exceed vehicle kinematic limits. We originally developed MUONS for small to mid-size skid-steer autonomous ground vehicles with no suspension. In this work we examine how MUONS performs on a simulated full-scale vehicle with complex suspension elements. By comparing the performance of the full-scale and mid-size vehicle we aim to identify the critical vehicle linkages that must be included in our simulation model. We also aim to understand the necessary changes and modifications required to adapt MUONS to full-scale Ackerman steering autonomous ground vehicles with complex suspensions.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.