Overview
Proper placement of the base of a robot manipulator is an important issue in many robotics applications. For instance, in manufacturing, the base location of a manipulator has a significant impact on the cycle time of tasks such as spot welding and inspection. An automated means to determine the best placement can both increase the throughput of workcells and reduce set-up time. This work investigates methods that employ randomized motion planning techniques to search for the best placement efficiently.
An Iterative Robot Placement Algorithm
Our algorithm computes simultaneously a base location and a corresponding collision-free path that are optimized with respect to the execution time of tasks. The algorithm has been tested on both synthetic examples and real-life CAD data from the automotive industry.
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| Four test scenes (click to enlarge the images). | |||
Quicktime movie (1.0 MB).
Download the Quicktime viewer.
There is a QuickTime movie for one of the computed examples. The movie clip first shows a PUMA arm at some arbitrary initial base location and executing a path computed by a randomized motion planner, and then shows the manipulator performing the same task after path and base location optimization.
References
- D. Hsu, J.C. Latombe, and S. Sorkin. Placing a robot manipulator amid obstacles for optimized execution. In Proc. IEEE Int. Symp. on Assembly & Task Planning, pp. 280–285, 1999.
PDF
People
- David Hsu
- Jean-Claude Latombe
- Rajeev Motwani
- Stephen Sorkin
Acknowledgments
This research has been supported by a grant from SIMA (Stanford Integrated Manufacturing Association), ARO MURI grant DAAH04-96-1-007, a Microsoft Graduate Fellowship, General Motors Corp., and Deneb Robotics Inc.