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Predictive joint motion limiting in robotic applications

Published online by Cambridge University Press:  02 March 2021

Edward Red  and
Brian Fielding
Edward Red
Affiliation:
Department of Mechanical Engineering, Brigham Young University, 435 CTB, P.O. Box 24201, Provo, Utah84602–4201 (USA)
Brian Fielding
Affiliation:
Department of Mechanical Engineering, Brigham Young University, 435 CTB, P.O. Box 24201, Provo, Utah84602–4201 (USA)
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Summary

Three joint space algorithms slow the Cartesian path motion when it appears that joint motion is approaching a joint, speed, or acceleration limit. All three algorithms use quadratic curve fitting to predict where the joint motion is heading, followed by a prediction as to how much time would elapse until a limit is reached.

If a joint motion limit is encountered in the time-to-stop the Cartesian motion, these algorithms reduce the Cartesian speed using pulsed speed settings so that the robot or machine tool will have the necessary time to come to a complete stop. The joint space velocity and acceleration control algorithms set the override Cartesian speed to either full or some reduced speed, several times a second. This allows the joints to reach, but not exceed, their maximum velocity and accelerations limit, while remaining within the physical joint limits.

Keywords

Direct controlJoint motion limitingRobotic applications
Type
Research Article
Information
Robotica , Volume 21 , Issue 5 , October 2003 , pp. 531 - 540
Copyright
Copyright © Cambridge University Press 2003

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References

1. Bassett, C.P., Jensen, C.G., Bosley, J., Luo, Y., Red, W.E. and Evans, M., “Direct Machining Architectures Using CAD-CAM Generative Methods”, Proceedings of the IASTED International Conference Control and Applications (May 24–27, 2000) pp. 287–294.Google Scholar
2. Bassett, C.P., et. al., “Direct Machining: A New Paradigm for Machining Data Transfer”, ASME 5th Design for Manufacture Conference, Baltimore, Maryland (Sept. 10–13, 2000) paper # DFM-1498.CrossRefGoogle Scholar
3. Red, W.E., Evans, M., Jensen, C.G., Bosley, J. and Luo, Y., “Motion Planning and Trajectory Control of a Direct Machining Application”, Proceedings of the IASTED International Conference Control and Applications (May 24–27, 2000) pp. 484–489.Google Scholar
4. Chiacchio, P. and Chiaverini, S., “Coping With Joint Velocity Limits In First-Order Inverse Kinematics Algorithms: Analysis And Real-Time Implementation”, Robotica 13, Part 5, 515–519 (1995).CrossRefGoogle Scholar
5. Chiaverini, S. and Fusco, G., “A New Inverse Kinematics Algorithm With Path Tracking Capability Under Velocity and Acceleration Constraints”, Proceedings of the 38th Conference on Decision and Control (May, 1999) pp. 2064–2069.Google Scholar
6. Zlajpah, L., “On Time Optimal Path Control of Manipulators with Bounded Joint Velocities and Torques”, International Conference on Robotics and Automation (April, 1996) pp. 1572–1577.Google Scholar
7. Ohishi, K. and Someno, T., “Robust Robot Manipulator Control with Autonomous Consideration Algorithm for Torque Saturation”, Advanced Robotics 12 Nos 7 & 8, 755–769 (1999).CrossRefGoogle Scholar
8. Chan, T. and Dubey, R., “A Weighted Least-Norm Solution Based Scheme for Avoiding Joint Limits for Redundant Joint Manipulators”, IEEE Transactions on Robotics and Automation 11, No. 2, 286–293 (April, 1995).CrossRefGoogle Scholar
9. Park, J., Chung, W. and Youm, Y., “Reconstruction of the Inverse Kinematic Solution Subject To Joint Kinematic Limits Using Kinematic Redundancy”, Advanced Robotics 11, No. 4, 377–395 (1997).CrossRefGoogle Scholar
10. Red, E., “A Dynamic Optimal Trajectory Generator for Cartesian Path Following”, Robotica 18, Part 5, 451–458 (2000).CrossRefGoogle Scholar
11. Fielding, B., “Predictive Joint Motion Limiting in Robotic Applications,” M.S. Thesis (Brigham Young University, April, 2002).Google Scholar
12. Newcastle University's Chemical and Process Engineering Web Server, “Dealing with Measurement Noise”, © M.T. Tham (1996–1998). See Web URL: http://lorien.ncl.ac.uk/ming/filter/fiewma.htm.Google Scholar
13. Nakamura, Y. and Hanafusa, H., “Inverse Kinematic Solutions with Singularity Robustness for Robot Manipulator Control”, Journal of Dynamic Systems, Measurement, and Control 108, No. 3, 163–171 (Sept. 1986).CrossRefGoogle Scholar
14. Yoshikawa, T., “Manipulatability of Robotic Mechanisms”, 2nd International Symposium of Robotics Research, Tokyo, Japan (1984) pp. 91–98.Google Scholar