25 citations · 25 across the 9 of their papers we have counts for
9 papers
Predictive Style Matching: Natural and Robust Humanoid Locomotion
Simeon Nedelchev, Ekaterina Chaikovskaia, Egor Davydenko +2
Reinforcement learning has become the prevailing approach to humanoid locomotion control: policies transfer reliably from simulation to hardware and recover gracefully from disturb…
Trajectory-based actuator identification via differentiable simulation
Vyacheslav Kovalev, Ekaterina Chaikovskaia, Egor Davydenko +1
Accurate actuation models are critical for bridging the gap between simulation and real robot behavior, yet obtaining high-fidelity actuator dynamics typically requires dedicated t…
Heuristic Step Planning for Learning Dynamic Bipedal Locomotion: A Comparative Study of Model-Based and Model-Free Approaches
William Suliman, Ekaterina Chaikovskaia, Egor Davydenko +1
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 f…
DecARt Leg: Design and Evaluation of a Novel Humanoid Robot Leg with Decoupled Actuation for Agile Locomotion
Egor Davydenko, Andrei Volchenkov, Vladimir Gerasimov +1
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 desi…
Achieving Precise and Reliable Locomotion with Differentiable Simulation-Based System Identification
Vyacheslav Kovalev, Ekaterina Chaikovskaia, Egor Davydenko +1
Accurate system identification is crucial for reducing trajectory drift in bipedal locomotion, particularly in reinforcement learning and model-based control. In this paper, we pre…
Benchmarking the Full-Order Model Optimization Based Imitation in the Humanoid Robot Reinforcement Learning Walk
Ekaterina Chaikovskaya, Inna Minashina, Vladimir Litvinenko +4
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, an…
RoboKit-MV: an Educational Initiative
Azer Babaev, Ilya Osokin, Ilya Ryakin +5
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 w…
Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper
Egor Davydenko, Ivan Khokhlov, Vladimir Litvinenko +3
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 d…
Tiny-YOLO object detection supplemented with geometrical data
Ivan Khokhlov, Egor Davydenko, Ilya Osokin +4
We propose a method of improving detection precision (mAP) with the help of the prior knowledge about the scene geometry: we assume the scene to be a plane with objects placed on i…