Reconfiguration of Squares Using a Constant Number of Moves Each
🤖 AI Summary
This study investigates the computational complexity of multi-robot reconfiguration under the constraint that each square-shaped robot is permitted only a constant number of sliding moves. By integrating techniques from computational complexity theory, geometric reasoning, and combinatorial optimization, the authors model and classify the constrained sliding motion planning problem. The primary contribution lies in establishing that the problem is NP-hard in its general form, while demonstrating the existence of an efficient algorithm for the special case where robots are unit-sized and the target configuration is unlabeled. These results delineate the theoretical boundaries of solvability in constrained multi-robot systems, highlighting how specific structural assumptions can render an otherwise intractable problem computationally feasible.
Application Category
📝 Abstract
Multi-robot motion planning is a hard problem. We investigate restricted variants of the problem where square robots are allowed to slide over an arbitrary curve to a new position only a constant number of times each. We show that the problem remains NP-hard in most cases, except when the squares have unit size and when the problem is unlabeled, i.e., the location of each square in the target configuration is left unspecified.
Problem
Research questions and friction points this paper is trying to address.
multi-robot motion planning
reconfiguration
square robots
NP-hard
constant moves
Innovation
Methods, ideas, or system contributions that make the work stand out.
multi-robot motion planning
reconfiguration
sliding squares
NP-hardness
unlabeled robots
🔎 Similar Papers
No similar papers found.
