27 research outputs found
Efficient Multi-Robot Motion Planning for Unlabeled Discs in Simple Polygons
We consider the following motion-planning problem: we are given unit
discs in a simple polygon with vertices, each at their own start position,
and we want to move the discs to a given set of target positions. Contrary
to the standard (labeled) version of the problem, each disc is allowed to be
moved to any target position, as long as in the end every target position is
occupied. We show that this unlabeled version of the problem can be solved in
time, assuming that the start and target positions are at
least some minimal distance from each other. This is in sharp contrast to the
standard (labeled) and more general multi-robot motion-planning problem for
discs moving in a simple polygon, which is known to be strongly NP-hard
Efficient multi-robot motion planning for unlabeled discs in simple polygons
We consider the following motion-planning problem: we are given unit discs in a simple polygon with vertices, each at their own start position, and we want to move the discs to a given set of target positions. Contrary to the standard (labeled) version of the problem, each disc is allowed to be moved to any target position, as long as in the end every target position is occupied. We show that this unlabeled version of the problem can be solved in time, assuming that the start and target positions are at least some minimal distance from each other. This is in sharp contrast to the standard (labeled) and more general multi-robot motion planning problem for discs moving in a simple polygon, which is known to be strongly NP-hard
On the hardness of unlabeled multi-robot motion planning
In unlabeled multi-robot motion planning several interchangeable robots
operate in a common workspace. The goal is to move the robots to a set of
target positions such that each position will be occupied by some robot. In
this paper, we study this problem for the specific case of unit-square robots
moving amidst polygonal obstacles and show that it is PSPACE-hard. We also
consider three additional variants of this problem and show that they are all
PSPACE-hard as well. To the best of our knowledge, this is the first hardness
proof for the unlabeled case. Furthermore, our proofs can be used to show that
the labeled variant (where each robot is assigned with a specific target
position), again, for unit-square robots, is PSPACE-hard as well, which sets
another precedence, as previous hardness results require the robots to be of
different shapes
Finding a needle in an exponential haystack: Discrete RRT for exploration of implicit roadmaps in multi-robot motion planning
We present a sampling-based framework for multi-robot motion planning which
combines an implicit representation of a roadmap with a novel approach for
pathfinding in geometrically embedded graphs tailored for our setting. Our
pathfinding algorithm, discrete-RRT (dRRT), is an adaptation of the celebrated
RRT algorithm for the discrete case of a graph, and it enables a rapid
exploration of the high-dimensional configuration space by carefully walking
through an implicit representation of a tensor product of roadmaps for the
individual robots. We demonstrate our approach experimentally on scenarios of
up to 60 degrees of freedom where our algorithm is faster by a factor of at
least ten when compared to existing algorithms that we are aware of.Comment: Kiril Solovey and Oren Salzman contributed equally to this pape
Types of Cooperation Robots in Robotic Complex
Приведена классификация сотрудничества роботов-манипуляторов. Описаны подходы к разработке программного обеспечения. Рассмотрены функции для реализации сотрудничества роботов и стратегии планирования траекторий роботов при совместной работе. Эффективность предложенной методики подтверждается результатами моделирования.= The article gives an categorizes the cooperation of robotic manipulators. Approaches to software development are described. The functions for realization of cooperation of robots and strategies for planning robot trajectories in collaboration are considered. The effectiveness of the proposed approach is confirmed by the results of modeling