Paper Info
Title
Rapid motion planning algorithm for optimal UVMS interventions in semi-structured environments using GPUs
Abstract
In this work, a novel local motion planning algorithm is presented, for underwater vehicle manipulator systems (UVMS) that perform autonomous underwater inspection operations. An optimization problem is formulated considering the collision avoidance, the approximation of the given task curve and critical optimization criteria. The searching method is based on an evolutionary algorithm and it is able to generate a local motion plan using continuously updated sensor information. The working environment is represented by a Bump-surface entity, constantly updated by a parallel algorithm implemented on a graphical processing unit (GPU). A trained artificial neural network is used for the fast approximation of the considered dexterity index. The local planner can cope with unknown obstacles inside the workspace while executing the task and pursuing high performance configurations in the free space. A welding inspection on an underwater tube structure is considered as the validation scenario, while a UVMS with a mounted six degrees of freedom manipulator is assigned to perform the task. Local motion planning method for UVMS interventions in semi-structured environments.Motion planning optimization towards efficient and dexterous manipulations.Bump-surface entity to map the workspace; collision checking is performed instantly.Bump-surface rapidly updated based on parallel GPU programming.A speedup up to 123×for the parallel implementation compared to the serial approach.
Year
DOI
Venue
2015
10.1016/j.robot.2015.06.005
Robotics and Autonomous Systems
Keywords
DocType
Volume
Motion planning,UVMS,GPU,CUDA,Evolutionary algorithms,Dexterous manipulation,Bump surfaces
Journal
74
Issue
ISSN
Citations 
PA
0921-8890
0
PageRank 
References 
Authors
0.34
16
4
Name
Order
Citations
PageRank
Panagiotis Sotiropoulos112.05
Vasileios Kolonias2101.86
Nikos A. Aspragathos324337.69
Efthymios Housos421914.71