72 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
Coordination-free Multi-robot Path Planning for Congestion Reduction Using Topological Reasoning
We consider the problem of multi-robot path planning in a complex, cluttered
environment with the aim of reducing overall congestion in the environment,
while avoiding any inter-robot communication or coordination. Such limitations
may exist due to lack of communication or due to privacy restrictions (for
example, autonomous vehicles may not want to share their locations or intents
with other vehicles or even to a central server). The key insight that allows
us to solve this problem is to stochastically distribute the robots across
different routes in the environment by assigning them paths in different
topologically distinct classes, so as to lower congestion and the overall
travel time for all robots in the environment. We outline the computation of
topologically distinct paths in a spatio-temporal configuration space and
propose methods for the stochastic assignment of paths to the robots. A fast
replanning algorithm and a potential field based controller allow robots to
avoid collision with nearby agents while following the assigned path. Our
simulation and experiment results show a significant advantage over shortest
path following under such a coordination-free setup.Comment: 30 pages, 9 figure
A Scalable Strategy for Open Loop Magnetic Control of Microrobots Using Critical Points
A novel scalable strategy for open loop control of ferromagnetic microrobots on a plane using a scalable array of electromagnets is presented. Instead of controlling the microrobot directly, we create equilibrium points in the magnetic force field that are stable and attractive on the plane in which the microrobot is to be controlled. The microrobot moves into these equilibrium points rapidly in presence of low viscous forces, and thus controlling the equilibrium points let us control the microrobot precisely. An unit/cell in the array of electromagnets allows precise control of the microrobot in the unit/cell’s domain. Motion synthesis across multiple overlapping domains allows control of the microrobot in large regions across the array. We perform numerical analysis and demonstrate the control of the ferromagnetic microrobot using the proposed method through simulations
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