activity
20162024
most citedSafe Interval Path Planning With Kinodynamic Constraints

4 citations · 8 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.AI2024

Improved Anonymous Multi-Agent Path Finding Algorithm

Zain Alabedeen Ali, Konstantin Yakovlev

We consider an Anonymous Multi-Agent Path-Finding (AMAPF) problem where the set of agents is confined to a graph, a set of goal vertices is given and each of these vertices has to…

cs.AI20232 cited

Learn to Follow: Decentralized Lifelong Multi-agent Pathfinding via Planning and Learning

Alexey Skrynnik, Anton Andreychuk, Maria Nesterova +2

Multi-agent Pathfinding (MAPF) problem generally asks to find a set of conflict-free paths for a set of agents confined to a graph and is typically solved in a centralized fashion.…

cs.AI2023

Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results

Yelisey Pitanov, Alexey Skrynnik, Anton Andreychuk +2

In this work we study a well-known and challenging problem of Multi-agent Pathfinding, when a set of agents is confined to a graph, each agent is assigned a unique start and goal v…

cs.AI20234 cited

Safe Interval Path Planning With Kinodynamic Constraints

Zain Alabedeen Ali, Konstantin Yakovlev

Safe Interval Path Planning (SIPP) is a powerful algorithm for solving single-agent pathfinding problem when the agent is confined to a graph and certain vertices/edges of this gra…

cs.AI20162 cited

Resolving Spatial-Time Conflicts In A Set Of Any-angle Or Angle-constrained Grid Paths

Konstantin Yakovlev, Anton Andreychuk

We study the multi-agent path finding problem (MAPF) for a group of agents which are allowed to move into arbitrary directions on a 2D square grid. We focus on centralized conflict…

cs.AI2016

Psychologically inspired planning method for smart relocation task

Aleksandr I. Panov, Konstantin Yakovlev

Behavior planning is known to be one of the basic cognitive functions, which is essential for any cognitive architecture of any control system used in robotics. At the same time mo…