Egor Davydenko
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View article: DecARt Leg: Design and Evaluation of a Novel Humanoid Robot Leg with Decoupled Actuation for Agile Locomotion
DecARt Leg: Design and Evaluation of a Novel Humanoid Robot Leg with Decoupled Actuation for Agile Locomotion Open
In this paper, we propose a novel design of an electrically actuated robotic leg, called the DecARt (Decoupled Actuation Robot) Leg, aimed at performing agile locomotion. This design incorporates several new features, such as the use of a …
View article: Heuristic Step Planning for Learning Dynamic Bipedal Locomotion: A Comparative Study of Model-Based and Model-Free Approaches
Heuristic Step Planning for Learning Dynamic Bipedal Locomotion: A Comparative Study of Model-Based and Model-Free Approaches Open
This work presents an extended framework for learning-based bipedal locomotion that incorporates a heuristic step-planning strategy guided by desired torso velocity tracking. The framework enables precise interaction between a humanoid rob…
View article: Full‐Body Optimization‐Based Bipedal Walking Control With Task‐Space Inverse Dynamics and Virtual Constraints
Full‐Body Optimization‐Based Bipedal Walking Control With Task‐Space Inverse Dynamics and Virtual Constraints Open
Achieving stable and versatile bipedal locomotion remains a major challenge in robotics, with applications in personal assistance, healthcare, and search and rescue. The hybrid zero dynamics (HZD) framework, based on virtual constraints, h…
View article: Reinforcement Learning-Based Footstep Control for Humanoid Robots on Complex Terrain
Reinforcement Learning-Based Footstep Control for Humanoid Robots on Complex Terrain Open
We propose a Reinforcement Learning (RL)-based footstep planning framework that enables a bipedal robot to achieve stable locomotion over challenging terrain. At its core, a learned step-following policy executes footstep commands with var…
View article: Benchmarking the Full-Order Model Optimization Based Imitation in the Humanoid Robot Reinforcement Learning Walk
Benchmarking the Full-Order Model Optimization Based Imitation in the Humanoid Robot Reinforcement Learning Walk Open
When a gait of a bipedal robot is developed using deep reinforcement learning, reference trajectories may or may not be used. Each approach has its advantages and disadvantages, and the choice of method is up to the control developer. This…
View article: RoboKit-MV: an Educational Initiative
RoboKit-MV: an Educational Initiative Open
In this paper, we present a robot model and code base for affordable education in the field of humanoid robotics. We give an overview of the software and hardware of a robot that won several competitions with the team RoboKit in 2019-2021,…
View article: Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper
Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper Open
This article is devoted to the features that were under development between RoboCup 2019 Sydney and RoboCup 2021 Worldwide. These features include vision-related matters, such as detection and localization, mechanical and algorithmic novel…