Back to Search Start Over

Trajectory optimization for autonomous mobile robots in ITER.

Authors :
Vale, Alberto
Fonte, Daniel
Valente, Filipe
Ribeiro, Isabel
Source :
Robotics & Autonomous Systems. Jun2014, Vol. 62 Issue 6, p871-888. 18p.
Publication Year :
2014

Abstract

Abstract: The Cask and Plug Remote Handling System (CPRHS) is one of the remote handling systems that will operate in the International Thermonuclear Experimental Reactor (ITER), transporting heavy and highly activated in-vessel components between the Tokamak Building and the Hot Cell Building, the two main buildings of the nuclear facility. The CPRHS has similar dimensions as an autobus, maximum weight of 100 tons, with kinematics of a rhombic-like vehicle (two drivable and steerable wheels) and has to move in cluttered environments. Two main approaches for trajectory optimization were developed and implemented aiming at providing smooth paths that maximize the clearance to obstacles taking into account the flexibility of rhombic-like vehicles: line guidance (same path for both wheels) and free roaming (different paths for each wheel). The line guidance approach includes maneuvers when necessary and the ability of maximizing the common parts of different paths used in the most of the nominal operations. Free roaming is mainly used when line guidance is not possible, namely in rescue operations. Both approaches were implemented in a standalone application that receives 2D CAD models of the buildings and returns the best trajectories, including a report of the most risky points of collision and the swept volume of the vehicle along the missions. This paper also presents the main results of these approaches applied in the models of the real scenarios, crucial to proceed with the construction of the Tokamak Building. Conclusions and future work are presented and discussed. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09218890
Volume :
62
Issue :
6
Database :
Academic Search Index
Journal :
Robotics & Autonomous Systems
Publication Type :
Academic Journal
Accession number :
95714726
Full Text :
https://doi.org/10.1016/j.robot.2014.01.007