Reliability and Fault Tolerance in Collective Robot Systems

Collective robotic systems (or, equivalently, multi-robot teams) have many potential advantages over single-robot systems, including increased speed of task completion through parallelism; improved solutions for tasks that are inherently distributed in space, time, or functionality; cheaper solutions for complex applications that can be addressed with multiple specialized robots, rather than all-capable monolithic entities; and, increased robustness and reliability through redundancy [Parker (2008)]. Of course these advantages do not come for free. Indeed, collective robot systems often experience a variety of problems that do not arise in single-robot solutions. First, even though the individual robot cost and complexity may be less in a collective solution, determining how to manage the complete system may be more difficult and complex because of the lack of centralized control or of a centralized repository of global information [Goldman and Zilberstein (2004)]. Further, collective robotic systems may require increased communication to coordinate all the robots in the system [Xuan et al. (2001)]. Increasing the number of robots can lead to higher levels of interference [Goldberg and Mataric (1997)], as the robots must act without complete knowledge of their teammates' intentions. Additionally, collective systems will often experience increased uncertainty about the state of the system as a whole [Mataric (1995)]. If not properly handled, all of these challenging issues can lead to a collective system that is unreliable and faulty [Parker (1998)]. Fortunately, a number of techniques have been developed to realize the advantages of collective robotic systems while countering many of the possible disadvantages. This chapter discusses the challenges of achieving collective robotic systems that are reliable and

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