Learn More
—We present an on-board robotic module which can determine relative positions among miniature robots. The module uses high-frequency modulated infrared emissions to enable nearby robots to determine the range, bearing, and message of the sender with a rapid update rate. A CSMA protocol is employed for scalable operation. We describe a technique for(More)
— Within the field of multi-robot systems, multi-robot search is one area which is currently receiving a lot of research attention. One major challenge within this area is to design effective algorithms that allow a team of robots to work together to find their targets. Recently, techniques have been adopted for multi-robot search from the Particle Swarm(More)
— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers in an automated fashion. In multi-robot systems, robots learning in parallel can share information to dramatically increase the evolutionary(More)
Swarm intelligence, and swarm robotics in particular, are reaching a point where leveraging the potential of communication within an artificial system promises to uncover new and varied directions for interesting research without compromising the key properties of swarm-intelligent systems such as self-organization, scalability, and robustness. However, the(More)
— We characterize and improve an existing infrared relative localization/communication module used to find range and bearing between robots in small-scale multi-robot systems. Modifications to the algorithms of the original system are suggested which offer better performance. A mathematical model which accurately describes the system is presented and allows(More)
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fashion. In multi-robot systems, robots operating in parallel can potentially learn at a much faster rate by sharing(More)
We present an adaptive strategy for a group of robots engaged in the localization of multiple targets. The robotic search algorithm is inspired by chemotaxis behavior in bacteria, and the algorithmic parameters are updated using a distributed implementation of the Particle Swarm Optimization technique. We explore the efficacy of the adaptation , the impact(More)