Motion planning

About: Motion planning is a research topic. Over the lifetime, 32846 publications have been published within this topic receiving 553548 citations.

Modular Self-reconfigurable Robot Systems: Challenges and Opportunities for the Future

Abstract: T he field of modular self-reconfigurable robotic systems addresses the design, fabrication , motion planning, and control of autonomous kinematic machines with variable morphology. Beyond conventional actuation, sensing, and control typically found in fixed-morphology robots, self-reconfigurable robots are also able to deliberately change their own shape by rearranging the connectivity of their parts in order to adapt to new circumstances, perform new tasks, or recover from damage. Over the last two decades, the field of modular robotics has advanced from proof-of-concept systems to elaborate physical implementations and simulations. The goal of this article is to outline some of this progress and identify key challenges and opportunities that lay ahead. Modular robots are usually composed of multiple building blocks of a relatively small repertoire, with uniform docking interfaces that allow transfer of mechanical forces and moments, electrical power, and communication throughout the robot. The modular building blocks often consist of some primary structural actuated unit and potentially some additional specialized units such as grippers, feet, wheels, cameras, payload, and energy storage and generation units. Figure 1 illustrates such a system in the context of a potential application. Modular self-reconfigurable robotic systems can be generally classified into several architectural groups by the geometric arrangement of their units. Several systems exhibit hybrid properties. ◆ Lattice Architectures: Lattice architectures have units that are arranged and connected in some regular, three-dimensional pattern, such as a simple cubic or hexagonal grid. Control and motion can be executed in parallel. Lattice architectures usually offer simpler reconfiguration, as modules move to a discrete set of neighboring locations in which motions can be made open-loop. The computational representation can also be more easily scaled to more complex systems. ◆ Chain/Tree Architectures: Chain/tree architectures have units that are connected together in a string or tree topology. This chain or tree can fold up to become space filling, but the underlying architecture is serial. Through articulation, chain architectures can potentially reach any point or orientation in space, and are therefore more versatile but computationally more difficult to represent and analyze and more difficult to control. ◆ Mobile Architectures: Mobile architectures have units that use the environment to maneuver around and can either hook up to form complex chains or lattices or form a number of smaller robots that execute coordinated movements and together form a larger " virtual " network. Control of all three types of modular systems can be centralized …

Dynamic path planning in sensor-based terrain acquisition

Abstract: The terrain acquisition problem is formulated as that of continuous motion planning, and no constraints are imposed on obstacle geometry. Two algorithms are described for acquiring planar terrains with obstacles of arbitrary shape. Estimates of the algorithm performance are derived as upper bounds on the lengths of generated paths. >

Motion planning in dynamic environments using the relative velocity paradigm

Abstract: A simple and efficient approach to the computation of avoidance maneuvers among moving obstacles is presented. The method is discussed for the case of a single maneuvering object avoiding several obstacles moving on known linear trajectories. The original dynamic problem is transformed into several static problems using the relative velocity between the maneuvering object and each obstacle. The static problems are converted into a single problem by means of a vector transformation, and the set of velocity vectors guaranteeing the avoidance of all the obstacles is computed. Within this set, the best maneuver for the particular approach can be selected. The geometric background of this approach is developed for both 2-D and 3-D cases, and the method is applied to an example of a 3-D avoidance maneuver. >

Motion strategies for maintaining visibility of a moving target

Abstract: We introduce the problem of computing robot motion strategies that maintain visibility of a moving target in a cluttered workspace. Both motion constraints (as considered in standard motion planning) and visibility constraints (as considered in visual tracking) must be satisfied. Additional criteria, such as the total distance traveled, can be optimized. The general problem is divided into two categories, on the basis of whether the target is predictable. For the predictable case, an algorithm that computes optimal, numerical solutions is presented. For the more challenging case of a partially-predictable target, two online algorithms are presented that each attempt to maintain future visibility with limited prediction. One strategy maximizes the probability that the target will remain in view in a subsequent time step, and the other maximizes the minimum time in which the target could escape the visibility region. We additionally discuss issues resulting from our implementation and experiments on a mobile robot system.