A javascript visualization for Emergent Taxis (a swarm of low-capable robots finds a light source)
- Simply hit
start / freeze
to observe the swarm locate the light beacon. - Hit
reset
to start a new run. - Hit
download data
to download csv data for an executed run. - Use the controls on the top right to experiment with parameters.
n_agents
: Number of agentsunit
: Unit sizealpha
: Target fraction of agents to have within communication range.r_avoid_light
: Agent avoidance radius in light.r_avoid_shad
: Agent avoidance radius in shadow.
Emergence describes 'how stupid things get smart together' (after a great kurzgesagt video). Think: A single ant is not capable of much, but a whole ant colony can achieve impressive things.
We will observe a swarm of minimalist, low-capable robots slowly moving towards a light source. Each individual agent is not capable of doing so, but together they can locate the light (hence the emergent).
Read original papers and find additional information here:
Julien Nembrini, Alan Winfield, Chris Melhuish. Minimalist Coherent Swarming of Wireless Networked Autonomous Mobile Robots. Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats, pages 373–382, Cambridge, MA, USA, 2002. MIT Press.
J. D. Bjerknes, A. F. Winfield and C. Melhuish, An Analysis of Emergent Taxis in a Wireless Connected Swarm of Mobile Robots. 2007 IEEE Swarm Intelligence Symposium, Honolulu, HI, 2007, pp. 45-52, https://doi.org/10.1109/SIS.2007.368025.
Heiko Hamann, Heinz Wörn, A framework of space–time continuous models for algorithm design in swarm robotics. Swarm Intelligence 2, 209–239 (2008). https://doi.org/10.1007/s11721-008-0015-3