Pavel A. Makarov
Papers
1
Total Citations
4
H-Index
1
About
Pavel A. Makarov is a researcher in robotics and control systems, with a focus on real-time motion planning and geometric approaches to autonomous interception. His work centers on developing model-free algorithms that enable robots to interact with dynamic objects without relying on complex environmental models, a key challenge in fields like service robotics and autonomous navigation. In his most-cited paper, "A Model-Free Algorithm of Moving Ball Interception by Holonomic Robot Using Geometric Approach" (2019), Makarov introduced a novel geometric method that allows holonomic robots to intercept moving targets using only visual feedback, bypassing the need for predictive models. This contribution has garnered 4 citations, reflecting its niche but practical impact on simplifying robot control in unstructured settings. While his citation count is modest, Makarov’s work is notable for its emphasis on low-complexity, real-time solutions that can be readily implemented in physical systems, bridging theory and application. His research holds promise for advancing autonomous systems in areas such as sports robotics, warehouse automation, and human-robot interaction, where quick, adaptive responses to moving objects are critical.
Research Focus
Key Achievements
Top Papers
- 1