Computational Principles of Mobile Robotics

Although the vast majority of mobile robotic systems involve a single robot operating alone in its environment, a growing number of researchers are considering the challenges and potential advantages of having a group of robots cooperate in order to complete some required task. For some specific robotic tasks, such as exploring an unknown planet, pushing objects, or cleaning up toxic waste, it has been suggested that rather than send one very complex robot to perform the task, it would more effective to send a number of smaller, simpler robots. Such a collection of robots is sometimes described as a swarm, a colony, or a collective, or the robots may be said to exhibit cooperative behavior. Using multiple robots rather than a single robot can have several advantages and leads to a variety of design tradeoffs. Collectives of simple robots may be simpler in terms of individual physical design than a larger, more complex robot, and thus the resulting system can be more economical, more scalable, and less susceptible to task failure.

Robot collectives build on a wide range of research results in distributed algorithms, sensor networks, and biology. As a consequence, the literature on robot collectives spans a wide range with a wide variety of assumptions and goals. One common theme, however, is the desire to develop technology that will enable a group of robots to solve a common problem.