Robot swarming over the Internet

Abstract

We consider cooperative control of robots involving two different testbed systems in remote locations in different time zones, with communication on the internet. The goal is to have all robots properly follow a leader defined on one of the testbeds, while maintaining non-overlapping positions within each swarm and between swarms, assuming they are superimposed in the same virtual space. A dual-testbed design is developed involving real robots and remote network communication, performing a cooperative swarming algorithm based on a modified Morse Potential. Extensive experimental results were obtained with real internet communication and virtual testbeds running in each lab. The communication protocol was designed to minimize loss of packets, and average transfer delays are within tolerance limits for practical applications. We ran several experiments, with intentional packet loss, that illustrate the degradation of the results in the case of modest and severe packet loss. The novelty of this work is its experimental aspect involving long range network communication across a large distance via the internet. The work raises a series of interesting theoretical problems.

Swarming on Random Graphs

“…The cost of each step in the computation would then be of O(N log N) while still retaining the qualitative aspects of the N 2 coupling. This observation might also prove useful when using the compromise model, or a related model, in a distributed control setting [15,16]. For problems in which communication between agents is expensive, such as mobile robot technology that uses a wireless signal for communication, the reduction to O(log N) interactions per agent would then allow use of the compromise model in a setting where the usual O(N) cost is prohibitively expensive.…”

Topologically induced swarming phase transition on a 2D percolated lattice

“…More generally, topological disorder poses a significant challenge to systems that engage in any collective decision making process such as slime molds solving mazes [41,42] and quorum sensing bacteria [43,44]. Topological disorder is also intrinsic in virtual environments where collective processes are important such as social networks, the internet and scientific citation networks [45][46][47] as well as artificial groups in real environments such as robotic drones exploring unknown territory [48,49]. It is interesting to speculate whether such general collective decision making systems can benefit from tempering purely consensus driven decisions with moderate amounts of antisocial behavior to overcome topological disorder.…”

A high-performance millirobot for swarm-behaviour studies: Swarm-topology estimation

“…26,46,49,51,55,56 Estimating the locations of swarm members, for purposes such as those discussed above, is termed swarm localization and is, typically, an online process. 26 Online localization can be carried out either using an external infrastructure 57,58 or on-board sensors, [59][60][61][62][63][64][65][66][67][68][69][70][71] where the latter is more robust as it eliminates reliance on structures or entities outside of the swarm. Range-based methods of localization using onboard sensors, which require the robots in the swarm to directly measure their relative proximity and bearing with respect to other neighbouring robots, are common.…”