Title :
Accelerated Patch Sorting by a Robotic Swarm
Author_Institution :
Dept. of Comput. Sci., Memorial Univ. of Newfoundland, St. John´s, NL, Canada
Abstract :
We introduce a new method for distributed object sorting by a swarm of robots. The patch sorting task involves pushing randomly distributed objects into homogeneous clusters. Most existing methods do not make use of vision and are therefore restricted to sensing the objects that lie immediately in front of the robot. We utilize vision both to sense the presence of a cluster and judge its homogeneity, and to seek out distant clusters or isolated objects to pick up. The objects to be sorted are coloured pucks. We present results using a realistic simulation which shows that a simple guidance strategy based on the size of distant clusters can dramatically accelerate the sorting process.
Keywords :
robot vision; sorting; accelerated patch sorting; coloured pucks; distant clusters; distributed object sorting; guidance strategy; homogeneous clusters; isolated objects; robot vision; robotic swarm; Clustering algorithms; Green products; Image color analysis; Robot kinematics; Robot sensing systems; Sorting; biologically-inspired robotics; clustering; patch sorting; swarm robotics;
Conference_Titel :
Computer and Robot Vision (CRV), 2012 Ninth Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4673-1271-4
DOI :
10.1109/CRV.2012.48