Rustam Stolkin

About

Rustam Stolkin is a leading researcher in robotics, specializing in robotic manipulation, autonomous systems, and nuclear decommissioning robotics. His work spans a remarkable breadth of challenges, from intelligent grasping and motion planning to human-robot collaboration and hazardous environment automation. Stolkin has made particularly significant contributions to nuclear robotics, pioneering the application of advanced autonomous and teleoperated robotic systems to the pressing global challenge of nuclear waste handling. His 2016 pilot study on nuclear decommissioning robotics (83 citations) and his weakly-supervised approach to nuclear waste object detection (103 citations) have helped establish a rigorous scientific foundation for a field that has historically relied on rudimentary remote operation. His research into dynamic grasping of moving objects (102 citations) further demonstrates his expertise in enabling robots to collaborate fluidly with human co-workers. Beyond nuclear applications, Stolkin has advanced the fundamentals of robotic manipulation through work on object behavior prediction, inertial parameter estimation (54 citations), push manipulation planning, and hybrid motion/force control. His contributions to trajectory optimization and omnidirectional mobile robots round out a portfolio that consistently bridges theoretical rigor with real-world industrial impact, making him an influential figure in modern robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   A Novel Weakly-Supervised Approach for RGB-D-Based Nuclear Waste Object Detection

   103 citations · 2018
2. 2
   Dynamic grasp and trajectory planning for moving objects

   102 citations · 2018
3. 3
   Towards advanced robotic manipulation for nuclear decommissioning: A pilot study on tele-operation and autonomy

   83 citations · 2016
4. 4
   Motion Planning and Control of an Omnidirectional Mobile Robot in Dynamic Environments

   66 citations · 2021
5. 5
   Learning to predict how rigid objects behave under simple manipulation

   63 citations · 2011
6. 6
   Guiding Trajectory Optimization by Demonstrated Distributions

   57 citations · 2017
7. 7
   Estimation and Exploitation of Objects' Inertial Parameters in Robotic Grasping and Manipulation: A Survey

   54 citations · 2019
8. 8
   Two-level RRT planning for robotic push manipulation

   50 citations · 2012
9. 9
   Hybrid motion/force control: a review

   47 citations · 2017
10. 10
    Mixed-initiative variable autonomy for remotely operated mobile robots

    47 citations · 2021

Key Collaborators

Contact & Links