19 citations · 90 across the 34 of their papers we have counts for
43 papers
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.…
Evaluation of Safety Constraints in Autonomous Navigation with Deep Reinforcement Learning
Brian Angulo, Gregory Gorbov, Aleksandr Panov +1
While reinforcement learning algorithms have had great success in the field of autonomous navigation, they cannot be straightforwardly applied to the real autonomous systems withou…
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…
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…
Policy Optimization to Learn Adaptive Motion Primitives in Path Planning with Dynamic Obstacles
Brian Angulo, Aleksandr Panov, Konstantin Yakovlev
This paper addresses the kinodynamic motion planning for non-holonomic robots in dynamic environments with both static and dynamic obstacles -- a challenging problem that lacks a u…
TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers
Daniil Kirilenko, Anton Andreychuk, Aleksandr Panov +1
Heuristic search algorithms, e.g. A*, are the commonly used tools for pathfinding on grids, i.e. graphs of regular structure that are widely employed to represent environments in r…