Alexey Kolker
Papers
7
Total Citations
38
H-Index
4
About
Alexey Kolker is a robotics researcher focused on advancing human-robot interaction through multimodal sensing and control. His work centers on tactile sensing, sensor calibration, and vision-based object manipulation, with a particular emphasis on safe and intuitive collaboration between humans and robots. Kolker's most cited paper, "An Optical Tactile Sensor for Measuring Force Values and Directions for Several Soft and Rigid Contacts" (2016, 11 citations), introduces a high-sensitivity 3D tactile sensor critical for robots handling fragile objects. He also developed an efficient extrinsic calibration method for LiDAR, camera, and industrial robot systems (2020, 6 citations), enabling accurate perception in collaborative environments. His research on hand segmentation using convolutional neural networks (2019, 5 citations) and model-free object transfer between human and robot hands using vision/force control (2014, 4 citations) addresses key challenges in seamless human-robot interaction. Kolker's contributions to visual servoing, demonstrated through an inverted pendulum control system (2013, 4 citations), further showcase his expertise in real-time robotic control. With a cumulative citation count of 38 across his most influential works, Kolker's research has practical implications for manufacturing, assistive robotics, and safe automation, making him a notable figure in the field of robotic manipulation and sensor integration.
Research Focus
Key Achievements
Top Papers
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- 6Robot visual servoing using the example of the inverted pendulum4 citations · 2013
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