Summary. To explore the effects of different simple communications strategies on performance of robot teams, we have conducted a set of foraging experiments using real robots (the Minnesota Distributed Autonomous Robotic Team). Our experimental results show that more complex communication strategies do not necessarily improve task completion times, but tend to reduce variance in performance.

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A cutom per-siun of rhe The reasons for all this research activity are threefold. First of all, time is of the essence in search and rescue. The likelihood of survival drops off very rapidly after the fust 48

The costs of developing mobile robot teams can be reduced if they are designed to exploit swarm techniques. In this methodology many simple homogeneous units solve complex tasks through emergent behavior. The challenge lies in selecting an appropriate control strategy for the individual units. Complexity in design costs both money and time, therefore a control strategy should be just complex enough to perform the task successfully in a variety of environments, relative to some performance measure. To explore the effects of control strategies and environmental factors on performance, we have conducted two sets of foraging experiments using real robots (the Minnesota Distributed Autonomous Robotic Team). The first set of experiments tested the efficacy of localization capabilities, in addition to the effects of team size and target distribution. The second set tested the efficacy of communication. We found that more complex control strategies do not necessarily improve task completion times, however they can reduce variance in performance measures. This can be valuable information for designers who need to assess the potential costs and benefits of increased complexity in design.

Small-size robots provide access and maneuverability in the tight confines of highly rubbled and uncertain environments such as those encountered in Urban Search and Rescue (USAR). Small size also provides easy portability and deployability and the potential for redundancy through multi-robot teaming. Unfortunately, small size does not diminish the data demands of these applications, such as high-resolution imagery and other forms of high bandwidth data. Furthermore, achieving redundancy in tight environments requires wireless operation to avoid the entanglement of tethers, but wireless communication links have proven unreliable in such environments. The net effect of this is a set of robust networking requirements that include high bandwidth, low latency, and low power with multi-hop routing in a sparse and highly volatile network configuration, which has been collectively difficult to achieve. Our metric for benchmarking these requirements is a stream of uncompressed 320x240, 24-bit color images updated at 1 frame per second (roughly 1.8 Mbps -image compression is not the focus of this research as it only serves to increase the possible resolution or frame rate). No existing ad hoc wireless sensor network approaches have been able to achieve these requirements. Wi-Fi requires high power and size and does not have the latency, while Zig-bee does not have the bandwidth. Instead, this work focuses on augmenting the Bluetooth protocol, which is master/slave based, with a hybrid, multi-hop routing protocol. Bluetooth has the desired low power and high bandwidth characteristics, but lacks multi-hop routing and rapid recovery. In this paper, a hybrid routing protocol for ad hoc multi-robot networking is described that features: 1) high-bandwidth, 2) low power, and 3) low latency of data traffic for sparse, highly volatile networks -exactly what is required for large teams of highly distributed, small-scale robots. Furthermore, this paper compares simulations and robot implementations of different routing protocols over Bluetooth sensor networks and demonstrates the viability of our protocol as a wireless network solution for multi-robot teams characterized by high mobility in difficult RF environments. To the best of our knowledge, the work presented in this paper is the first attempt at comparison of different routing protocols for real robots with physical experiments over Bluetooth sensor networks.