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Aleksandr Onegin

dblp:395/6490 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
path planning
0.912025
Safe Interval Randomized Path Planning For Manipulators · ICAPS 2025
Robotics › Motion planning and robot control › path planning › search-based path planning
safe interval path planning
0.912025
Safe Interval Randomized Path Planning For Manipulators · ICAPS 2025
Robotics › Motion planning and robot control › motion planning
sampling-based motion planning
0.912025
Safe Interval Randomized Path Planning For Manipulators · ICAPS 2025

Methods — techniques the papers use, named apart from their topics

heuristic search · 0.9bidirectional RRT-Connect · 0.9
YearPublicationVenuePosition
2025 Safe Interval Randomized Path Planning For Manipulators
abstract
Planning safe paths in 3D workspace for high DoF robotic systems, such as manipulators, is a challenging problem, especially when the environment is populated with the dynamic obstacles that need to be avoided. In this case the time dimension should be taken into account that further increases the complexity of planning. To mitigate this issue we suggest to combine safe-interval path planning (a prominent technique in heuristic search) with the randomized planning, specifically, with the bidirectional rapidly-exploring random trees (RRT-Connect) -- a fast and efficient algorithm for high-dimensional planning. Leveraging a dedicated technique of fast computation of the safe intervals, we end up with an efficient planner dubbed SI-RRT. We compare it with the state of the art and show that SI-RRT consistently outperforms the competitors both in runtime and solution cost.
Nuraddin Kerimov, Aleksandr Onegin, Konstantin S. Yakovlev
ICAPS2