M.V. Nosikov

About

M.V. Nosikov is a leading researcher in the field of robotic control systems, with a specialized focus on radiation-proof manipulators and human-robot interaction for hazardous environments. Their work addresses the critical challenge of replacing outdated human-driven copying-type manipulators with advanced, remotely operated robotic systems for use in heavy nuclear fields. Nosikov’s major contributions include the development of automatic and manual control algorithms for 6-degree-of-freedom radiation-proof manipulators, as detailed in their 2018 paper (4 citations), which outlines the architecture, functional specifications, and operating modes of these systems. They have also pioneered the integration of neural network algorithms to monitor and restrict the gripper’s work area, enhancing safety during manipulator movement in high-radiation zones (2017, 4 citations). Additionally, Nosikov has designed innovative operator training systems for human-controlled arm manipulators, with two related papers (2018 and 2019, each with 2 citations) focusing on improving operator proficiency and safety. With a total of 12 citations across their most-cited works, Nosikov’s research is foundational for advancing robotic autonomy and safety in extreme industrial environments, making their work essential for students and researchers in nuclear robotics and intelligent control systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Automatic and Manual Control Algorithms of Radiation-Proof Manipulators

   4 citations · 2018
2. 2
   Control System of the RobotManipulator with Use of Neural Network Algorithms of Restriction of Work Area of the Gripper

   4 citations · 2017
3. 3
   Architecture of Human-controlled Arm Manipulator Operator Training System

   2 citations · 2018
4. 4
   The Architecture of Human-Controlled Arm Manipulator Operator Training System

   2 citations · 2019

Key Collaborators

Contact & Links