Collective Robotic Site Preparation

Abstract

Robotic site preparation has been identified as an integral precursor to human landings on Mars. Many species of social insect carry out the site preparation task when they construct their nests. A site preparation algorithm was developed based on the nest construction behavior of a particular species of ant, Leptothorax albipennis. In this paper, we present a new approach to modeling the temporal behavior of a multiple-robot system and apply it to our construction algorithm. In order to validate our model, experiments with multiple physical robots were conducted. Not only did the results of our experiments closely follow the predictions of our model, but the sites prepared by our robots appeared very similar to the nests built by the ants that were our inspiration.

Cooperative food transport in the Neotropical ant, Pheidole oxyops

“…Real world applications may also require lifting, especially of delicate items or work on irregular terrain, and lessons learned from this and future studies may provide inspiration for solving such lifting problems. The benefits of ant-inspired systems may be of prime importance in robotic applications where direct intervention is impossible or impractical, such as deep sea or extraterrestrial engineering (Huntsberger et al, 2000;Parker and Zhang, 2006;Woern et al, 2006). Cooperatively lifting objects is something that humans and their machines need to do regularly.…”

Autonomous construction using scarce resources in unknown environments

“…Robots provide an excellent real-world test ground for validating biological behaviour models, for instance investigating the relationship between model parameters and resulting emergent structures, such as clusters of pucks (Melhuish et al 1998), cleared areas (Parker and Zhang 2006) or walls (Melhuish et al 1999;Stewart and Russell 2006). This line of research emphasizes simplicity and minimalism, which is reflected in the experimental setups.…”

An Adaptive Particle Swarm Optimization Algorithm for Distributed Search and Collective Cleanup in Complex Environment

“…According to Figures 4,5,6, and 7, the robot swarm based on our modified PSO algorithm performs as good as usual. No matter how many the obstacles are, robots can complete the task perfectly.…”

“…Distributed multirobot systems demand group coherence and group competence [4]. Due to its robustness, flexibility, and reliability, the distributed coordination is desirable for multirobot systems under dynamic environment [5,6]. Therefore, the main challenge for multirobot systems is to develop intelligent robots which can adapt their behaviors based on interaction with the environment and other robots, so as to become more proficient in their tasks in new situations [7,8].…”