On Bends and Distances of Paths among Obstacles in Two-Layer Interconnection Model

We consider problems of finding assorted rectilinear paths among rectilinear obstacles in a two-layer interconnection model according to the number of bends and the 1-layer distance (y-distance). Using a horizontal wave-front approach, optimal /spl theta/(e log e) time algorithms are presented to find the shortest path and the minimum-bend path using linear space, and to find the shortest minimum-bend path and the minimum-bend shortest path using O(e log e) space, where e is the number of obstacle edges. By the same approach, we also derive an algorithm for finding a shortest two-layer distance (xy-distance) minimum-bend path in optimal /spl theta/(e log e) time using O(e log e) space

Heterogeneous Self-Reconfiguring Robotics

Self-reconfiguring (SR) robots are modular systems that can autonomously change shape, or reconfigure, for increased versatility and adaptability in unknown environments. In this thesis, we investigate planning and control for systems of non-identical modules, known as heterogeneous SR robots. Although previous approaches rely on module homogeneity as a critical property, we show that the planning complexity of fundamental algorithmic problems in the heterogeneous case is equivalent to that of systems with identical modules. Primarily, we study the problem of how to plan shape changes while considering the placement of specific modules within the structure. We characterize this key challenge in terms of the amount of free space available to the robot and develop a series of decentralized reconfiguration planning algorithms that assume progressively more severe free space constraints and support reconfiguration among obstacles. In addition, we compose our basic planning techniques in different ways to address problems in the related task domains of positioning modules according to function, locomotion among obstacles, self-repair, and recognizing the achievement of distributed goal-states. We also describe the design of a novel simulation environment, implementation results using this simulator, and experimental results in hardware using a planar SR system called the Crystal Robot. These results encourage development of heterogeneous systems. Our algorithms enhance the versatility and adaptability of SR robots by enabling them to use functionally specialized components to match capability, in addition to shape, to the task at hand