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In recent years there has been in increasing interest in distributed robotic systems. In such a system, a task is not completed by a single robot but instead by a team of collaborating robots. Team members may exchange sensor information, may help each other to scale obstacles, or may collaborate to manipulate heavy objects. A team of robots has distinct advantages over single robots with respect to actuation as well as sensing. When manipulating or carrying large objects, the load can be distributed over several robots so that each robot can be built much smaller, lighter, and less expensive. As for sensing, a team of robots can perceive its environment from multiple disparate viewpoints. A single robot, on the other hand, can only sense its environment from a single viewpoint, even when it is equipped with a large array of different sensing modalities. There are many tasks for which distributed viewpoints are advantageous: surveillance, monitoring, demining, plume detection, etc. Distributed robotic systems require a new design philosophy. Traditional robots are designed with a broad array of capabilities (sensing, actuation, communication, and computation). Often, the designers will even add redundant components to avoid system failure from a single fault. The resulting systems are large, complex, and expensive. For robot teams, the design can be approached from a completely different angle, namely: "Build simple inexpensive robots with limited capabilities that can accomplish the goal reliably through cooperation." Each individual robot may not be very capable, but as a team they can still accomplish useful tasks. This results in less expensive robots that are easier to maintain and debug. Moreover, since each robot is expendable, reliability can be obtained in numbers; that is, if a single robot fails, only limited capabilities are lost, and the team can still continue the task with remaining robots. Because the size of a robot determines to a large extent its capabilities, we are developing a hierarchical robot team. As is shown in Figure 1, the team consists of large All Terrain Vehicles (ATVs), medium-sized tank-like robots (based on a remote control Tamiya tank model), and centimeter scale Millibots (6×6×6cm). The ATVs have a range of up to 100 miles. They are capable of transporting a user with multiple smaller robots to the area of interest. Once the team has arrived, the ATV with its multiple Pentiums can serve as a main processing node for high-level planning. It may control and coordinate multiple mid-sized robots each of which in turn heads a team of Millibots. Such a hierarchical organization allows us to combine the autonomy and computation power of the large ATVs with the distributed sensing capabilities of a large number of covertly operating Millibots. To take full advantage of the distributed sensing capabilities of Millibot teams, it is important that these robots be inexpensive, lightweight, and small. Small and lightweight robots can be easily carried by their larger counterparts higher-up in the robot hierarchy. They can maneuver through small openings and into tight corners to observe areas that are not accessible to larger robots. Small robots are also less noticeable allowing for covert operations in hostile territory. By building them inexpensively, they can be deployed in large numbers to achieve dense sensing coverage, adaptability at the team level, and fault tolerance. To achieve both small size and a expansive capabilities, we are developing Millibots capable of carrying specialized platforms. Instead of equipping every robot with every sensor, computation, or communication capability, we are building robots that are each specialized for a particular aspect of the task. In one type of scenario, the robot team may be composed of robots with various range and position sensors but only limited computation capabilities. In this case these robots act as distributed sensor platforms remotely controlled by a team leader who performs the high-level planning. In another task, the same group of Millibots may be equipped with computational modules that provide local processing of data. The choice of platforms is dependent only on the task. To achieve this level of specialization without the need for a huge repository of robots, we have chosen to develop the Millibots in a modular fashion. Each of the subsystems (computation, communication, sensors, and mobility) has been implemented as a self-contained module that can be configured with other modules to obtain a Millibot that is specifically designed for the given task. |
   A hierarchial team of robots |
