Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Designing emergent behaviors: from local interactions to collective intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Terrain coverage with ant robots: a simulation study
Proceedings of the fifth international conference on Autonomous agents
Efficient and inefficient ant coverage methods
Annals of Mathematics and Artificial Intelligence
Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Coordinating microscopic robots in viscous fluids
Autonomous Agents and Multi-Agent Systems
Cooperative Cleaners: A Study in Ant Robotics
International Journal of Robotics Research
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Covering a continuous domain by distributed, limited robots
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Review: Of robot ants and elephants: A computational comparison
Theoretical Computer Science
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Ant robots have very low computational power and limited memory. They communicate by leaving pheromones in the environment. In order to create a cooperative intelligent behavior, ants may need to get together; however, they may not know the locations of other ants. Hence, we focus on an ant variant of the rendezvous problem, in which two ants are to be brought to the same location in finite time. We introduce two algorithms that solve this problem for two ants by simulating a bidirectional search in different environment settings. An algorithm for an environment with no obstacles and a general algorithm that handles all types of obstacles. We provide detailed discussion on the different attributes, size of pheromone required, and the performance of these algorithms.