Search Results for author: Konstantin Yakovlev

Found 30 papers, 13 papers with code

Safe Interval Path Planning With Kinodynamic Constraints

1 code implementation1 Feb 2023 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 graph are blocked at certain time intervals due to dynamic obstacles that populate the environment.

TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers

1 code implementation22 Dec 2022 Daniil Kirilenko, Anton Andreychuk, Aleksandr Panov, Konstantin Yakovlev

To this end, we suggest learning the instance-dependent heuristic proxies that are supposed to notably increase the efficiency of the search.

Analysis Of The Anytime MAPF Solvers Based On The Combination Of Conflict-Based Search (CBS) and Focal Search (FS)

no code implementations20 Sep 2022 Ilya Ivanashev, Anton Andreychuk, Konstantin Yakovlev

Moreover, anytime variant of CBS does exist that applies Focal Search (FS) to the high-level of CBS - Anytime BCBS.

Pathfinding in stochastic environments: learning vs planning

1 code implementation PeerJ Computer Science 2022 Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Aleksandr Panov

Within planning, an agent constantly re-plans and updates the path based on the history of the observations using a search-based planner.

POGEMA: Partially Observable Grid Environment for Multiple Agents

1 code implementation22 Jun 2022 Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Aleksandr I. Panov

We introduce POGEMA (https://github. com/AIRI-Institute/pogema) a sandbox for challenging partially observable multi-agent pathfinding (PO-MAPF) problems .

Augmenting GRIPS with Heuristic Sampling for Planning Feasible Trajectories of a Car-Like Robot

no code implementations15 Aug 2021 Brian Angulo, Konstantin Yakovlev, Ivan Radionov

The results of the experimental evaluation provide a clear evidence that the success rate of the suggested algorithm is up to 40% higher compared to the original GRIPS and hits the bar of 90%, while its runtime is lower.

Motion Planning

Towards Time-Optimal Any-Angle Path Planning With Dynamic Obstacles

no code implementations14 Apr 2021 Konstantin Yakovlev, Anton Andreychuk

Path finding is a well-studied problem in AI, which is often framed as graph search.

Improving Continuous-time Conflict Based Search

1 code implementation24 Jan 2021 Anton Andreychuk, Konstantin Yakovlev, Eli Boyarski, Roni Stern

Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally solving classical multi-agent path finding (MAPF) problems, where time is discretized into the time steps.

Multi-Agent Path Finding

Map-merging Algorithms for Visual SLAM: Feasibility Study and Empirical Evaluation

no code implementations12 Sep 2020 Andrey Bokovoy, Kirill Muraviev, Konstantin Yakovlev

Simultaneous localization and mapping, especially the one relying solely on video data (vSLAM), is a challenging problem that has been extensively studied in robotics and computer vision.

Navigate Simultaneous Localization and Mapping

A Combination of Theta*, ORCA and Push and Rotate for Multi-agent Navigation

1 code implementation3 Aug 2020 Stepan Dergachev, Konstantin Yakovlev, Ryhor Prakapovich

We study the problem of multi-agent navigation in static environments when no centralized controller is present.

Revisiting Bounded-Suboptimal Safe Interval Path Planning

1 code implementation1 Jun 2020 Konstantin Yakovlev, Anton Andreychuk, Roni Stern

Safe-interval path planning (SIPP) is a powerful algorithm for finding a path in the presence of dynamic obstacles.

GAN Path Finder: Preliminary results

2 code implementations5 Aug 2019 Natalia Soboleva, Konstantin Yakovlev

2D path planning in static environment is a well-known problem and one of the common ways to solve it is to 1) represent the environment as a grid and 2) perform a heuristic search for a path on it.

Image Generation

Real-time Vision-based Depth Reconstruction with NVidia Jetson

1 code implementation16 Jul 2019 Andrey Bokovoy, Kirill Muravyev, Konstantin Yakovlev

Vision-based depth reconstruction is a challenging problem extensively studied in computer vision but still lacking universal solution.

Simultaneous Localization and Mapping

Multi-Agent Pathfinding with Continuous Time

1 code implementation16 Jan 2019 Anton Andreychuk, Konstantin Yakovlev, Dor Atzmon, Roni Stern

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide.

eLIAN: Enhanced Algorithm for Angle-constrained Path Finding

no code implementations2 Nov 2018 Anton Andreychuk, Natalia Soboleva, Konstantin Yakovlev

This problem is harder to solve than the one when shortest paths of any shape are sought, since the planer's search space is substantially bigger as multiple search nodes corresponding to the same location need to be considered.

Path Finding for the Coalition of Co-operative Agents Acting in the Environment with Destructible Obstacles

no code implementations2 Jul 2018 Anton Andreychuk, Konstantin Yakovlev

The problem of planning a set of paths for the coalition of robots (agents) with different capabilities is considered in the paper.

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

no code implementations25 Jun 2018 Andrey Bokovoy, Konstantin Yakovlev

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision.

Simultaneous Localization and Mapping

Two Techniques That Enhance the Performance of Multi-robot Prioritized Path Planning

no code implementations3 May 2018 Anton Andreychuk, Konstantin Yakovlev

We introduce and empirically evaluate two techniques aimed at enhancing the performance of multi-robot prioritized path planning.


Applying MAPP Algorithm for Cooperative Path Finding in Urban Environments

no code implementations20 Jul 2017 Anton Andreychuk, Konstantin Yakovlev

The paper considers the problem of planning a set of non-conflict trajectories for the coalition of intelligent agents (mobile robots).

Original Loop-closure Detection Algorithm for Monocular vSLAM

no code implementations15 Jul 2017 Andrey Bokovoy, Konstantin Yakovlev

Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays.

Loop Closure Detection Simultaneous Localization and Mapping

Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm

1 code implementation12 Mar 2017 Konstantin Yakovlev, Anton Andreychuk

This algorithm is then used as part of a prioritized multi-agent planner AA-SIPP(m).

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

no code implementations9 Aug 2016 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.

Multi-Agent Path Finding

Psychologically inspired planning method for smart relocation task

no code implementations27 Jul 2016 Aleksandr I. Panov, Konstantin Yakovlev

On the subsymbolic level the task of path planning is considered and solved as a graph search problem.

Behavior and path planning for the coalition of cognitive robots in smart relocation tasks

no code implementations27 Jul 2016 Aleksandr I. Panov, Konstantin Yakovlev

In this paper we outline the approach of solving special type of navigation tasks for robotic systems, when a coalition of robots (agents) acts in the 2D environment, which can be modified by the actions, and share the same goal location.

Finetuning Randomized Heuristic Search For 2D Path Planning: Finding The Best Input Parameters For R* Algorithm Through Series Of Experiments

no code implementations3 Nov 2015 Konstantin Yakovlev, Egor Baskin, Ivan Hramoin

As a result we formulate a set of heuristic rules which can be used to initialize the values of R* parameters in a way that leads to algorithm's best performance.

Grid-based angle-constrained path planning

no code implementations5 Jun 2015 Konstantin Yakovlev, Egor Baskin, Ivan Hramoin

Square grids are commonly used in robotics and game development as spatial models and well known in AI community heuristic search algorithms (such as A*, JPS, Theta* etc.)

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