Assessment of Energy-Efficient and Model Based Control
Abstract
The US Army Research Laboratory's (ARLs) Robotics Collaborative Technology Alliance is a program intended to change robots from tools that Soldiers use into teammates with which Soldiers can work. One desired ability of such a teammate is the ability to operate in an energy-efficient manner on a variety of surfaces. To develop such a teammate, alliance researchers developed planning algorithms that incorporate knowledge of the vehicles steering and control system. These algorithms adapt their navigation to different types of terrain, learning appropriate parameter values by conducting a brief set of trial maneuvers, and are intended to enable the robot to operate in a manner that is more energy efficient. In June of 2016, ARL researchers conducted an assessment of this technology by comparing this planning algorithm to a traditional minimum-distance planning algorithm. This assessment found an overall improvement in energy efficiency, which was clearly visible when the systems operated on grass, but unclear when the systems operated on asphalt. Overall, the results suggest that the energy-efficient planner does have the potential to plan more energy-efficient paths.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 15, 2017
- Accession Number
- AD1035230
Entities
People
- Aneesh Sharma
- Camilo Ordóñez
- Craig Lennon
- Emmanuel G. Collins
- James Pace
- Jonathan Clark
- Mario Harper
- Marshal Childers
- Nikhil Gupta
- Ryan Kopinsky
Organizations
- United States Army Research Laboratory