Abstract
Robot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighboring robots. While current swarm implementations can be large in size (e.g., 1,000 robots), they are typically constrained to working in highly controlled indoor environments. Moreover, a common property of swarms is the underlying assumption that the robots act in close proximity of each other (e.g., 10 body lengths apart), and typically employ uninterrupted, situated, close-range communication for coordination. Many real world applications, including environmental monitoring and precision agriculture, however, require scalable groups of robots to act jointly over large distances (e.g., 1,000 body lengths), rendering the use of dense swarms impractical. Using a dense swarm for such applications would be invasive to the environment and unrealistic in terms of mission deployment, maintenance and post-mission recovery. To address this problem, we propose the sparse swarm concept, and illustrate its use in the context of four application scenarios. For one scenario, which requires a group of rovers to traverse, and monitor, a forest environment, we identify the challenges involved at all levels in developing a sparse swarm—from the hardware platform to communication-constrained coordination algorithms—and discuss potential solutions. We outline open questions of theoretical and practical nature, which we hope will bring the concept of sparse swarms to fruition.
Highlights
Swarm robotics takes inspiration from observed behaviors of collective systems in nature (Camazine et al, 2003) to develop large-scale teams of robots with limited individual capabilities; the collective behavior emerging from the self-organized interactions between the many robots of a swarm allow it to solve complex tasks (Beni, 2004; Sahin, 2004)
We propose the concept of sparse swarms, where the group of robots interact while (i) not being in close proximity to each other, and/or (ii) it is not possible for information to rapidly propagate within the group
Robot swarms typically operate in highly controlled indoor laboratory environments
Summary
Swarm robotics takes inspiration from observed behaviors of collective systems in nature (Camazine et al, 2003) to develop large-scale teams of robots with limited individual capabilities; the collective behavior emerging from the self-organized interactions between the many robots of a swarm allow it to solve complex tasks (Beni, 2004; Sahin, 2004). Packed robot swarms are inspired by social insect colonies, and rely on inter-robot physical interactions to complete their task In employing such swarms in real-world outdoor applications encompassing large areas, the end-user faces a number of challenges involving the deployment and maintenance of such large numbers of robots during the mission. Sparse swarms could be relevant in application scenarios, where the robots are operating in the order of 1, 000 body lengths apart under sporadic low-bandwidth communication constraints. In such scenarios, the robots would be likely be required to coordinate their activities via informational interactions rather than physical interactions
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