Quasi-real-time confined environment path generation for mobile robotic manipulator arms. (March 2018)

• Record Type: Journal Article
• Authors: Wall, David Galvão; Economou, John; Knowles, Kevin
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 232:Number 3(2018)
• Page Start: 270
• Page End: 284
• Publication Date: 2018-03
• Subjects: Robotic manipulator guidance -- environment mapping -- graph theory -- close-proximity obstacle avoidance; Mechanical engineering -- Periodicals; Automatic control -- Periodicals; Systems engineering -- Periodicals; 621.3
• DOI: 10.1177/0959651817751317
• Languages: English
• ISSNs: 0959-6518

Abstract

Path generation for mobile robotic manipulator arms is challenging in dynamic environments because high-speed calculations are required to deal with fast-moving obstacles. A novel path-planning algorithm has been developed which solves in quasi-real time the problem of path generation in confined environments for interconnected multi-body systems, specifically a robotic manipulator arm with three links. The work presented in this article builds upon the previous work by reformulating the technique to increase the speed at which the algorithm is able to calculate a safe path. The complexity of the task space has increased substantially compared to previous work, and the algorithm has been reformulated to speed up the calculation in order to maintain or even improve its ability to plan a safe path in real time. The method is now able to calculate a safe path through environments significantly more quickly than the previous method, and the results presented in this article expand the complexity of the environment by a large amount and test the ability of the reformulated algorithm to still operate in real time, which the method achieves. It was found that the reformulated method reduces the calculation time for path generation exponentially when used to plan safe paths through test environments involving different numbers of obstacles. The new algorithm thus has the potential to facilitate path planning in challenging dynamic environments, such as those used in sensitive manufacturing and maintenance tasks as well as bomb disposal and similar applications.