single-jc.php

JACIII Vol.23 No.6 pp. 997-1003
doi: 10.20965/jaciii.2019.p0997
(2019)

Paper:

# Joint Trajectory Planning Based on Minimum Euclidean Distance of Joint Angles of a Seven-Degrees-of-Freedom Manipulator for a Sequential Reaching Task

## Yoshiaki Taniai and Tomohide Naniwa

Graduate School of Engineering, University of Fukui
3-9-1 Bunkyo, Fukui, Fukui 910-8507, Japan

October 30, 2017
Accepted:
June 25, 2019
Published:
November 20, 2019
Keywords:
optimal planning, sequential reaching task, 7-DOF manipulator, minimum Euclidean distance, movable ranges
Abstract

When a nuclear power disaster occurs at a nuclear power plant, it is hazardous for humans to enter the plant. If robots could remove radioactive substances adhering to a plane such as a plant wall, humans would be able to enter the plant to investigate the situation and to work. In this study, to efficiently remove radioactive substances from a wall with a manipulator, we examined joint trajectory planning based on the minimum Euclidean distance of joint angles of a seven-degrees-of-freedom (7-DOF) serial link manipulator for a sequential reaching task on a plane. We demonstrate the planning for the sequential reaching task, which is an iterative point-to-point reaching movement between positions on a plane. The joint angles for each target position were obtained based on the inverse kinematics for an arm angle, and the optimal arm angles within the constraints of the joint angles were computed by the sequential quadratic programming method. The optimal trajectories for the arm angles were compared with the trajectories of the joint angles that were the eight inverse kinematic solutions for a fixed arm angle. The result showed that through optimal planning, an efficient trajectory within the movable ranges of the joint angles could be obtained for the sequential reaching task.

Y. Taniai and T. Naniwa, “Joint Trajectory Planning Based on Minimum Euclidean Distance of Joint Angles of a Seven-Degrees-of-Freedom Manipulator for a Sequential Reaching Task,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.6, pp. 997-1003, 2019.
Data files:
References
1. [1] S. Kawatsuma, “Robots for Nuclear Emergency in Germany and France,” J. of the Robotics Society of Japan, Vol.32, No.1, pp. 25-31, 2014 (in Japanese).
2. [2] L. Morikawa, T. Hashimoto, N. Shimonabe, M. Yano, H. Onitsuka, and J. Fujita, “Development of the Remote Decontamination Robot “MHI-MEISTeR II” for an Upper Floor of Reactor Building in Fukushima Daiichi NPP,” E-J. of Advanced Maintenance, Vol.9, No.2, pp. 126-131, 2017.
3. [3] E. J. Minehara, “Laser decontamination device,” US Patent No.US9174304B2, 2015.
4. [4] K. Kreutz-Delgado, M. Long, and H. Seraji, “Kinematic Analysis of 7-DOF Manipulators,” Int. J. of Robotics Research, Vol.11, No.5, pp. 469-481, 1992.
5. [5] Y. Zhang, B. Cai, L. Zhang, and K. Li, “Bi-criteria Velocity Minimization of Robot Manipulators Using a Linear Variational Inequalities-Based Primal-Dual Neural Network and PUMA560 Example,” Advanced Robotics, Vol.22, No.13-14, pp. 1479-1496, 2008.
6. [6] M. Shimizu, H. Kakuya, W.-K. Yoon, K. Kitagaki, and K. Kosuge, “Analytical Inverse Kinematic Computation for 7-DOF Redundant Manipulators With Joint Limits and Its Application to Redundancy Resolution,” IEEE Trans. on Robotics, Vol.24, No.5, pp. 1131-1142, 2008.
7. [7] H. Asada and J.-J. E. Slotine, “Robot Analysis and Control,” John Wiley & Sons, 1986.
8. [8] P. E. Gill, W. Murray, and M. A. Saunders, “SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization,” SIAM Review, Vol.47, No.1, pp. 99-131, 2005.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Feb. 19, 2024