2015/11/24 by Jeff Jones, Jones, Jeff
Agricultural and Biological Sciences · Computer Science · Engineering · #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #Plant and Biological Electrophysiology Studies #Slime Mold and Myxomycetes Research #Topological and Geometric Data Analysis #cs.ET
paper · pdf · doi:10.48550/arxiv.1511.07654
2015 - Automated Guidance of Collective Movement in a Multi-Agent Model of Physarum polycephalum, Multi-Agent Models on Swarm Behaviour, Swarm 2015, 28-30 October, Kyoto, Japan
arxiv created 2015/11/24 · openalex publication_date 2015/11/24 · arxiv updated 2015/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Collective movement occurs in living systems where the simple movements of individual members of a pop- ulation are combined to generate movement of the collective as a whole, displaying complex dynamics which cannot be found in the component parts themselves. The plasmodium stage of slime mould Physarum polycephalum displays complex amoeboid movement during its foraging and hazard avoidance and its movement can be influenced by the spatial placement of attractant and repellent stimuli. Slime mould is attractive to robotics due to its simple component parts and the distributed nature of its control and locomotion mechanisms. We investigate methods of automated guidance of a multi-agent swarm collective along a pre-defined path to a goal location. We demonstrate a closed-loop feedback mechanism using attractant and repellent stimuli. We find that guidance by repellent stimuli (a light illumination mask) provides faster and more accurate guidance than attractant sources, which exhibit overshooting phenomena at path turns. The method allows traversal of convoluted arenas with challenging obstacles and provides an insight into how unconven- tional computing substrates may be hybridised with classical computing methods to take advantage of the benefits of both approaches.