Ant algorithms for discrete optimization
Artificial Life
Evolving adaptive pheromone path planning mechanisms
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Cooperative multi-robot box-pushing
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
Building patterned structures with robot swarms
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Stochastic strategies for a swarm robotic assembly system
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Complexity measures for distributed assembly tasks
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
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We address the distributed assembly of a structure by a team of homogeneous robots. We present an ant-colony-optimization (ACO) based algorithm to partition general 2- and 3-D assembly tasks into N separate subtasks. The objective is to determine an allocation or partitioning strategy that minimizes the workload imbalance between the robots that allow for maximum assembly parallelization. This objective is achieved by extending ACO to apply to a team of ants dividing a set of tasks, with pheromone marking connections between tasks guiding decisions on task allocation. We present simulation results for various 2-D and 3-D structures and discuss the advantages of the ACO formulation in the context of other existing approaches.