Research On Parallel Processing Techniques For Vision-navigation Of Mobile Robot

Environment sensing is one of the focus researches for mobile robot vision-navigation. In the field of robot navigation, vision-navigation has some advantages, such as high resolution, wide detection range, but a drawback of large computation costs for image processing. The real-time requirement of the robot can't be satisfied, if high resolution images are processed only by the onboard computer. So this thesis designs a grid system for image processing to process some time-consuming tasks, which can increase the speed of image processing.To implement the functionality of parallel image processing in the system, some study has been done. Firstly, in parallel image processing applications, major algorithms belong to data parallel iterative synchronous algorithms. So some co-scheduling algorithms are analyzed in detail, and a co-scheduling algorithm with reservations is proposed. This algorithm can shorten image processing time and improve resource utilization. Secondly grid belongs to non-specific NOWs and the workstation owner may submit to the machine a computation intensive task which competes with a parallel task for the resource. Under this situation, to accomplish tasks in time and successfully, a non-preemptive dynamic load balancing algorithm based on data migration is designed. This algorithm can ensure that parallel tasks shall be executed efficiently. Finally, this thesis designs a grid system for image processing whose scheduler employs the two algorithms mentioned above.The grid system for image processing provides some basic scheduling services, and deploys image processing algorithms as grid services which can be used by the system users. The system aims to minimize task response time and for high resource utilization, hence execution time of robot navigation tasks can be decreased, and high system throughput is provided. At last, the system provides the functionality of data migration, so navigation tasks can be accomplished in time and successfully. Thereby the grid system for image processing has some research value for improving the speed of image processing and satisfying the real-time requirement of robot navigation.