Papers
23
Total Citations
583
H-Index
16
About
Anton Zhilenkov is a prolific robotics researcher whose work spans soft robotics, intelligent control systems, and human-machine interaction. His research has made significant contributions to the field of bio-inspired and adaptive robotics, with a particular focus on bridging biological principles and engineering design. Zhilenkov's most cited work includes a groundbreaking 2021 study on an underwater bipedal soft robot inspired by the coconut octopus (56 citations), demonstrating his ability to translate natural locomotion strategies into functional robotic systems. His 2024 review on embodied intelligence in soft robotics (44 citations) further establishes him as a thought leader in understanding how physical form and intelligence co-evolve in robotic systems. Alongside soft robotics, he has advanced autonomous navigation, developing intelligent UAV navigation systems (31 citations) and terrain classification methods using hybrid deep learning architectures (50 citations). A recurring theme in Zhilenkov's research is human-robot interfacing: his early work on MEMS-based motion capture systems for controlling anthropomorphic robots (37 citations) laid important groundwork for intuitive teleoperation. His exploration of neural network architectures, including spiking neural networks (32 citations), reflects a forward-thinking approach to machine intelligence. Collectively accumulating over 380 citations, his body of work meaningfully advances the frontier of intelligent, adaptive, and biomimetic robotics.
Research Focus
Key Achievements
Top Papers
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- 3Exploring Embodied Intelligence in Soft Robotics: A Review44 citations · 2024
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- 7Prospects for the development and application of spiking neural networks32 citations · 2017
- 8Based on MEMS sensors man-machine interface for mechatronic objects control31 citations · 2017
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