5 citations · 8 across the 7 of their papers we have counts for
7 papers
Prometheus: Universal, Open-Source Mocap-Based Teleoperation System with Force Feedback for Dataset Collection in Robot Learning
S. Satsevich, A. Bazhenov, S. Egorov +4
This paper presents a novel teleoperation system with force feedback, utilizing consumer-grade HTC Vive Trackers 2.0. The system integrates a custom-built controller, a UR3 robotic…
Echo: An Open-Source, Low-Cost Teleoperation System with Force Feedback for Dataset Collection in Robot Learning
Artem Bazhenov, Sergei Satsevich, Sergei Egorov +2
In this article, we propose Echo, a novel joint-matching teleoperation system designed to enhance the collection of datasets for manual and bimanual tasks. Our system is specifical…
ViewVR: Visual Feedback Modes to Achieve Quality of VR-based Telemanipulation
A. Erkhov, A. Bazhenov, S. Satsevich +6
The paper focuses on an immersive teleoperation system that enhances operator's ability to actively perceive the robot's surroundings. A consumer-grade HTC Vive VR system was used…
Optimizing energy consumption for legged robot by adapting equilibrium position and stiffness of a parallel torsion spring
Danil Belov, Artem Erkhov, Farit Khabibullin +5
This paper is dedicated to the development of a novel adaptive torsion spring mechanism for optimizing energy consumption in legged robots. By adjusting the equilibrium position an…
HyperSurf: Quadruped Robot Leg Capable of Surface Recognition with GRU and Real-to-Sim Transferring
Sergei Satsevich, Yaroslav Savotin, Danil Belov +7
This paper introduces a system of data collection acceleration and real-to-sim transferring for surface recognition on a quadruped robot. The system features a mechanical single-le…
DogSurf: Quadruped Robot Capable of GRU-based Surface Recognition for Blind Person Navigation
Artem Bazhenov, Vladimir Berman, Sergei Satsevich +4
This paper introduces DogSurf - a newapproach of using quadruped robots to help visually impaired people navigate in real world. The presented method allows the quadruped robot to…
LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems
Artem Lykov, Maria Dronova, Nikolay Naglov +6
This paper introduces LLM-MARS, first technology that utilizes a Large Language Model based Artificial Intelligence for Multi-Agent Robot Systems. LLM-MARS enables dynamic dialogue…