Mikhail Gurchinsky

About

Mikhail Gurchinsky is a robotics researcher whose work spans swarm intelligence, anthropomorphic manipulation, and agricultural automation. His most cited paper, “Consensus achievement method for a robotic swarm about the most frequently feature of an environment” (12 citations), addresses decentralized multi-agent systems that distribute computation and communication across swarm elements, enhancing resilience to individual agent loss. Gurchinsky’s research on predictive hand trajectory assessment for copy-type control (11 citations) tackles the inverse dynamic problem, advancing robots for hazardous environments where human replacement is critical. He has developed energy-efficient path planning methods for anthropomorphic manipulators, addressing excessive energy consumption through quasi-optimal trajectory algorithms. His work on deep reinforcement learning with recurrent neural networks for greenhouse crop harvesting (4 citations) demonstrates practical applications in agricultural automation. Gurchinsky has also contributed to kinematic structure reconfiguration using greedy algorithms for modular robots, and multi-agent reinforcement learning for variable-number agent systems. His research consistently focuses on decentralized control, energy efficiency, and real-time trajectory optimization, with applications ranging from industrial manipulation to agricultural robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Consensus achievement method for a robotic swarm about the most frequently feature of an environment

   12 citations · 2020
2. 2
   Predictive Assessment of Operator's Hand Trajectory with the Copying Type of Control for Solution of the Inverse Dynamic Problem

   11 citations · 2019
3. 3
   Analysis of the Effectiveness Path Planning Methods and Algorithm for the Anthropomorphic Robot Manipulator

   8 citations · 2019
4. 4
   A Robotic Complex Control Method Based on Deep Reinforcement Learning of Recurrent Neural Networks for Automatic Harvesting of Greenhouse Crops

   4 citations · 2020
5. 5
   The Method of the Kinematic Structure Reconfiguration of a Multifunctional Modular Robot Based on the Greedy Algorithm

   2 citations · 2019
6. 6
   Kinematic analysis anthropomorphic gripper with group drive

   2 citations · 2020
7. 7
   Method of Controlling the Movement of an Anthropomorphic Manipulator in the Working Area With Dynamic Obstacle

   2 citations · 2020
8. 8
   METHOD FOR PLANNING THE OPTIMAL TRAJECTORY OF A THREE-LINK MANIPULATOR IN TRIDIMENSIONAL SPACE WITH AN OBSTACLE

   2 citations · 2018
9. 9
   Energy-Efficient Path Planning: Designed Software Implementation

   2 citations · 2019
10. 10
    Method of Multi-Agent Reinforcement Learning in Systems with a Variable Number of Agents

    1 citations · 2022

Key Collaborators

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