Pervasive networks of computing, communicating, and sensing devices will be embedded in future environments. These devices will include the likes of RFIDs, active badges, and sensor networks. For the most part, these devices are framed in the context of enabling and supporting human activities. We posit that these networks can also support, and be supported by, robot systems, and particularly mobile robot systems.

We want to understand the fundamental trade-offs concerning computation, communication, sensing, mobility, and manipluation in distributed robotic systems. Currently, we are investigating ways mobility can improve sensor networks and how pervasiveness can impact autonomous mobile robots.

We consider a heterogeneous system composed of many small, embedded, immobile, possibly sensor-less, communication nodes and larger mobile robots equipped with sensors and manipulators. We feel this heterogeneous system of embedded devices and mobile robots puts a natural constraint on the design space of multi-robot systems. The embedded network serves as a pervasive communication, computation, and coordination fabric, while the mobile robots provide sensing and actuation. We get some of the benefits of a robot swarm (pervasiveness) but in a much cheaper, more manageable way than with a fully mobile swarm.

We have implemented a hardware platform for building embedded networks to support mobile robots. The Gnats are low cost devices, allowing us to build a large number of them, and are highly configurable. The Gnats consist of four infrared (IR) emitters, four IR receivers, a thermometer, two visible light LEDs, a button, a Microchip PIC16F87 microcontroller, and a 3V battery. The simplicity of the platform makes it very inexpensive (less than $30), allowing us to build, and experiment with, a large number of devices. The platform is compatible with the LEGO Mindstorms robotics kit permitting the gnats to interact with RCX robots as well as with PCs via the LEGO IR dongle. We use the IR dongle to program hundreds of Gnats at once.

We are investigating a type of physical path planning using a large number of immobile robots. The algorithm essentially works as a distributed variant of the popular wave-front path planning algorithm, or a breadth-first search from the goal, propagating paths from the goal location. The embedded nodes make up the vertices of the path planning graph, and the network connections between them are the edges of the graph. Mobile robots can then use reactive navigation to traverse the graph by visiting the vertices (i.e. the embedded nodes) to the goal. The embedded network aides mobile robots in various tasks such as coverage, recruitment, and path planning. The embedded network provides nearly optimal path planning without the network nodes or the robots having global knowledge or localization capabilities. In addition, the network can provide paths for the robots in dynamic environments where paths are created and destroyed dynamically.