Leonid Butyrev
Papers
1
Total Citations
13
H-Index
1
About
Leonid Butyrev is a researcher specializing in robotics and artificial intelligence, with a particular focus on the intersection of deep reinforcement learning and autonomous mobile robot navigation. His most recognized contribution, "Deep Reinforcement Learning for Motion Planning of Mobile Robots" (2019), introduces a novel algorithm for motion and trajectory planning in nonholonomic mobile robots — systems with constrained movement dynamics that present significant challenges for traditional planning approaches. The work demonstrates how modern deep reinforcement learning techniques can enable robots to navigate from arbitrary initial states, accounting for position, velocity, and orientation simultaneously, representing a meaningful step forward in making autonomous robots more adaptable and robust in real-world environments. With 13 citations, Butyrev's research has attracted attention within the robotics and AI communities, reflecting its relevance to ongoing challenges in autonomous systems development. His work sits at a productive crossroads between theoretical machine learning advances and their practical application in robotics, contributing to the growing body of research aimed at making intelligent mobile robots capable of flexible, learned navigation without relying on hand-engineered planning rules.
Research Focus
Key Achievements
Top Papers
- 1Deep Reinforcement Learning for Motion Planning of Mobile Robots13 citations · 2019