Papers
25
Total Citations
167
H-Index
6
About
Kaloyan Yovchev is a robotics and control systems researcher whose work spans two complementary frontiers: advanced control theory for robotic manipulators and assistive service robotics for elderly and disabled populations. His most influential contribution, "State Space Constrained Iterative Learning Control for Robotic Manipulators" (2017, 31 citations), established a rigorous framework for high-precision trajectory tracking in constrained environments — a critical challenge in industrial robotics. He extended this line of inquiry through Constrained Output Iterative Learning Control (2020) and trajectory planning for redundant manipulators, systematically addressing the complexities of real-world robotic motion under physical limitations. Equally significant is Yovchev's dedication to socially impactful robotics. Through the ROBCO series of service robots, he has developed intelligent, cost-effective assistive platforms capable of supporting daily care tasks for people with mobility difficulties. His work on human-robot interaction (18 citations) and IoT-based remote communication systems (16 citations) demonstrates a commitment to making these technologies practically deployable. More recently, his research on the walking robot "Big Foot" signals a broadening into biomechanically inspired locomotion. With over 115 cumulative citations, Yovchev's research meaningfully bridges rigorous control engineering and humanitarian applications in robotics.
Research Focus
Key Achievements
Top Papers
- 1State Space Constrained Iterative Learning Control for Robotic Manipulators31 citations · 2017
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- 3Communication system for remote control of service robots16 citations · 2019
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- 5Cost-Oriented Mobile Robot Assistant for Disabled Care11 citations · 2015
- 6Constrained Output Iterative Learning Control8 citations · 2020
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