3 citations · 10 across the 13 of their papers we have counts for
11 papers · 1 filter
ORCESTRA: VLM-driven Visual Robot programming in Mixed Reality
Ivan Snegirev, Elizaveta Semenyakina, Mikhail Konenkov +3
ORCESTRA is a mixed-reality system for programming robot digital twins through no-code waypoint teaching and language-guided control. In a passthrough mixed-reality workspace, user…
AgenticFocus: Object-Preserving Mixed Reality Synthesis from Human FPV Video for Dexterous Humanoid Learning
Iaroslav Kolomiets, Miguel Altamirano Cabrera, Artem Lykov +6
Human egocentric video is a scalable supervision source for humanoid policy learning, but current pipelines struggle with hand-object occlusion, oversimplified motion, or specializ…
VersualRL: Closed-Loop Verbal Reinforcement Learning with Visual Execution Feedback for Task-Level Robot Planning
Dmitrii Plotnikov, Iaroslav Kolomiets, Dmitrii Maliukov +9
We introduce VersualRL, a closed-loop framework for task-level robot planning that uses visual execution feedback to iteratively refine executable Behavior Trees through structured…
PhysicalAgent: Towards General Cognitive Robotics with Foundation World Models
Artem Lykov, Jeffrin Sam, Hung Khang Nguyen +6
We introduce PhysicalAgent, an agentic framework for robotic manipulation that integrates iterative reasoning, diffusion-based video generation, and closed-loop execution. Given a…
Industry 6.0: New Generation of Industry driven by Generative AI and Swarm of Heterogeneous Robots
Artem Lykov, Miguel Altamirano Cabrera, Mikhail Konenkov +8
This paper presents the concept of Industry 6.0, introducing the world's first fully automated production system that autonomously handles the entire product design and manufacturi…
FlockGPT: Guiding UAV Flocking with Linguistic Orchestration
Artem Lykov, Sausar Karaf, Mikhail Martynov +4
This article presents the world's first rapid drone flocking control using natural language through generative AI. The described approach enables the intuitive orchestration of a f…
VR-GPT: Visual Language Model for Intelligent Virtual Reality Applications
Mikhail Konenkov, Artem Lykov, Daria Trinitatova +1
The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language…
VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes
Ziang Guo, Zakhar Yagudin, Artem Lykov +2
Recent research on Large Language Models for autonomous driving shows promise in planning and control. However, high computational demands and hallucinations still challenge accura…
CognitiveDog: Large Multimodal Model Based System to Translate Vision and Language into Action of Quadruped Robot
Artem Lykov, Mikhail Litvinov, Mikhail Konenkov +6
This paper introduces CognitiveDog, a pioneering development of quadruped robot with Large Multi-modal Model (LMM) that is capable of not only communicating with humans verbally bu…
CognitiveOS: Large Multimodal Model based System to Endow Any Type of Robot with Generative AI
Artem Lykov, Mikhail Konenkov, Koffivi Fidèle Gbagbe +6
This paper introduces CognitiveOS, the first operating system designed for cognitive robots capable of functioning across diverse robotic platforms. CognitiveOS is structured as a…
AirTouch: Towards Safe Human-Robot Interaction Using Air Pressure Feedback and IR Mocap System
Viktor Rakhmatulin, Denis Grankin, Mikhail Konenkov +4
The growing use of robots in urban environments has raised concerns about potential safety hazards, especially in public spaces where humans and robots may interact. In this paper,…