34,187 research outputs found
Optimal Path Planning in Distinct Topo-Geometric Classes using Neighborhood-augmented Graph and its Application to Path Planning for a Tethered Robot in 3D
Many robotics applications benefit from being able to compute multiple
locally optimal paths in a given configuration space. Examples include path
planning for of tethered robots with cable-length constraints, systems
involving cables, multi-robot topological exploration & coverage, and,
congestion reduction for mobile robots navigation without inter-robot
coordination. Existing paradigm is to use topological path planning methods
that can provide optimal paths from distinct topological classes available in
the underlying configuration space. However, these methods usually require
non-trivial and non-universal geometrical constructions, which are
prohibitively complex or expensive in 3 or higher dimensional configuration
spaces with complex topology. Furthermore, topological methods are unable to
distinguish between locally optimal paths that belong to the same topological
class but are distinct because of genus-zero obstacles in 3D or due to
high-cost or high-curvature regions. In this paper we propose an universal and
generalized approach to multi-class path planning using the concept of a novel
neighborhood-augmented graph, search-based planning in which can compute paths
in distinct topo-geometric classes. This approach can find desired number of
locally optimal paths in a wider variety of configuration spaces without
requiring any complex pre-processing or geometric constructions. Unlike the
existing topological methods, resulting optimal paths are not restricted to
distinct topological classes, thus making the algorithm applicable to many
other problems where locally optimal and geometrically distinct paths are of
interest. For the demonstration of an application of the proposed approach, we
implement our algorithm to planning for shortest traversible paths for a
tethered robot with cable-length constraint navigating in 3D and validate it in
simulations & experiments.Comment: 18 pages, 17 figure
A motion planner for nonholonomic mobile robots
This paper considers the problem of motion planning for a car-like robot (i.e., a mobile robot with a nonholonomic constraint whose turning radius is lower-bounded). We present a fast and exact planner for our mobile robot model, based upon recursive subdivision of a collision-free path generated by a lower-level geometric planner that ignores the motion constraints. The resultant trajectory is optimized to give a path that is of near-minimal length in its homotopy class. Our claims of high speed are supported by experimental results for implementations that assume a robot moving amid polygonal obstacles. The completeness and the complexity of the algorithm are proven using an appropriate metric in the configuration space R^2 x S^1 of the robot. This metric is defined by using the length of the shortest paths in the absence of obstacles as the distance between two configurations. We prove that the new induced topology and the classical one are the same. Although we concentrate upon the car-like robot, the generalization of these techniques leads to new theoretical issues involving sub-Riemannian geometry and to practical results for nonholonomic motion planning
Automated sequence and motion planning for robotic spatial extrusion of 3D trusses
While robotic spatial extrusion has demonstrated a new and efficient means to
fabricate 3D truss structures in architectural scale, a major challenge remains
in automatically planning extrusion sequence and robotic motion for trusses
with unconstrained topologies. This paper presents the first attempt in the
field to rigorously formulate the extrusion sequence and motion planning (SAMP)
problem, using a CSP encoding. Furthermore, this research proposes a new
hierarchical planning framework to solve the extrusion SAMP problems that
usually have a long planning horizon and 3D configuration complexity. By
decoupling sequence and motion planning, the planning framework is able to
efficiently solve the extrusion sequence, end-effector poses, joint
configurations, and transition trajectories for spatial trusses with
nonstandard topologies. This paper also presents the first detailed computation
data to reveal the runtime bottleneck on solving SAMP problems, which provides
insight and comparing baseline for future algorithmic development. Together
with the algorithmic results, this paper also presents an open-source and
modularized software implementation called Choreo that is machine-agnostic. To
demonstrate the power of this algorithmic framework, three case studies,
including real fabrication and simulation results, are presented.Comment: 24 pages, 16 figure
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