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Velin Kojouharov

dblp:340/3942 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Systems, architecture and hardware · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Motion planning and robot control · 36% Legged, aerial and field robots · 33% Robot manipulation · 31%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control
compliant motion control
0.912025
AquaMILR: Mechanical Intelligence Simplifies Control of Undulatory Robots in Cluttered Fluid Environments · ICRA 2025
Robotics › Legged, aerial and field robots
limbless locomotion
0.912025
AquaMILR: Mechanical Intelligence Simplifies Control of Undulatory Robots in Cluttered Fluid Environments · ICRA 2025
Robotics › Motion planning and robot control
robot control
0.912025
AquaMILR: Mechanical Intelligence Simplifies Control of Undulatory Robots in Cluttered Fluid Environments · ICRA 2025
Robotics › Robot manipulation › mechanical design
compliant mechanism
0.812024
Anisotropic body compliance facilitates robotic sidewinding in complex environments · ICRA 2024
Robotics › Legged, aerial and field robots › undulatory locomotion
sidewinding
0.812024
Anisotropic body compliance facilitates robotic sidewinding in complex environments · ICRA 2024
Robotics › Robot manipulation
soft robotics
0.812024
Anisotropic body compliance facilitates robotic sidewinding in complex environments · ICRA 2024

Methods — techniques the papers use, named apart from their topics

tension feedback control · 0.9open-loop control · 0.9cable-driven actuation · 0.9feedforward control · 0.8cable actuation · 0.8
YearPublicationVenuePosition
2025 AquaMILR: Mechanical Intelligence Simplifies Control of Undulatory Robots in Cluttered Fluid Environments
abstract
While undulatory swimming of elongate limbless robots has been extensively studied in open hydrodynamic environments, less research has been focused on limbless locomotion in complex, cluttered aquatic environments. Motivated by the concept of mechanical intelligence [1], where controls for obstacle navigation can be offloaded to passive body mechanics in terrestrial limbless locomotion, we hypothesize that principles of mechanical intelligence can be extended to cluttered hydrodynamic regimes. To test this, we developed an untethered limbless robot capable of undulatory swimming on water surfaces, utilizing a bilateral cable-driven mechanism inspired by organismal muscle actuation morphology to achieve programmable anisotropic body compliance. We demonstrated through robophysical experiments that, similar to terrestrial locomotion, an appropriate level of body compliance can facilitate emergent swim through complex hydrodynamic environments under pure open-loop control. Moreover, we found that swimming performance depends on undulation frequency, with effective locomotion achieved only within a specific frequency range. This contrasts with highly damped terrestrial regimes, where inertial effects can often be neglected. Further, to enhance performance and address the challenges posed by nondeterministic obstacle distributions, we incorporated computational intelligence by developing a real-time body compliance tuning controller based on cable tension feedback. This controller improves the robot's robustness and overall speed in heterogeneous hydrodynamic environments.
Tianyu Wang 0010, Nishanth Mankame, Matthew Fernandez, Velin Kojouharov, Daniel I. Goldman
ICRA4
2024 Anisotropic body compliance facilitates robotic sidewinding in complex environments
abstract
Sidewinding, a locomotion strategy characterized by the coordination of lateral and vertical body undulations, is frequently observed in rattlesnakes and has been successfully implemented by limbless robotic systems for effective movement across diverse terrestrial terrains. However, the integration of compliant mechanisms into sidewinding limbless robots remains less explored, posing challenges for navigation in complex, rheologically diverse environments. Inspired by a notable control simplification via mechanical intelligence in lateral undulation [1], which offloads feedback control to passive body mechanics and interactions with the environment, we present an innovative design of a mechanically intelligent limbless robot for sidewinding. This robot features a decentralized bilateral cable actuation system that resembles organismal muscle actuation mechanisms. We develop a feedforward controller that incorporates programmable body compliance into the sidewinding gait template. Our experimental results highlight the emergence of mechanical intelligence when the robot is equipped with an appropriate level of body compliance. This allows the robot to 1) locomote more energetically efficiently, as evidenced by a reduced cost of transport, and 2) navigate through terrain heterogeneities, all achieved in an open-loop manner, without the need for environmental awareness.
Velin Kojouharov, Tianyu Wang 0010, Matthew Fernandez, Jiyeon Maeng, Daniel I. Goldman
ICRA1