Large collections of robots have the potential to perform tasks collectively using distributed control algorithms. These algorithms require communication between robots to allow the robots to coordinate their behavior and act as a collective. In this paper we describe two algorithms which allow coordination between robots, but do not require physical environment marks such as pheromones. Instead, these algorithms rely on simple, local, low-bandwidth, direct communication between robots. We describe the algorithms and measure their performance in worlds with and without obstacles.978-1-4244-9318-0/10/$26.00
Swarm robotics utilizes a large number of simple robots to accomplish a task, instead of a single complex robot. Communications constraints often force these systems to be distributed and leaderless, placing restrictions on the types of algorithms which can be executed by the swarm. The performance of a swarm algorithm is aected by the environment in which the swarm operates. Dierent environments may call for dierent algorithms to be chosen, but often no single robot has enough information to make this decision. In this paper, we focus on foraging as a multi-robot task and present two distributed foraging algorithms, each of which performs best for dierent food locations. We then present a third adaptive algorithm in which the swarm as a whole is able to choose the best algorithm for the given situation by combining individual-level and distributed colony-level algorithm switching. We show that this adaptive method combines the benets of the other methods, and yields the best overall performance.
On-orbit servicing and assembly is a critical enabling technology for the advancement of large scale structures in space. The goal of the SWARM project (Synchronized Wireless Autonomous Reconfigurable Modules) is to develop and mature algorithms for autonomous docking and reconfiguration, to be used as the building blocks for autonomous servicing and assembly. Algorithms for approach, docking, and reconfiguration have been implemented and tested through a demonstration of the assembly of two telescope sub-apertures at Marshall Space Flight Center (MSFC) in July 2006. The algorithms developed for reconfiguration set the mass properties based on the configuration. Updatable parameters include the location of sensors and receivers with respect to the geometric center, thruster locations, and control gains specific to each configuration. To test these algorithms in a 2D environment, a ground testbed was developed to provide multiple docking ports and modular payload attachments. Hardware components include nodes, Universal Docking Ports, posts, sub-aperture mirrors, and a SPHERES satellite as the assembler tug. Testing at MSFC successfully demonstrated relative docking and reconfiguration. Valuable information was gained about the performance of the docking under friction, sensitivity to estimator initialization, thrust authority needed for different phases of the test, and control when CM changes during the test.
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