12 citations · 29 across the 52 of their papers we have counts for
59 papers
AutodidactWAM: Cross-Modal Self-Distillation from Generated Video to Robot Actions
Sergei Kurchev, Iaroslav Kolomiets, Miguel Altamirano Cabrera +2
World-action models (WAMs) such as Cosmos 3 jointly generate future video and robot actions from an observation and instruction. Adapting one such model with a lightweight LoRA fin…
AgenticTactileVLA: Contact-Guided Execution-Time Supervision for Generalizable Dexterous Manipulation without VLA Retraining
Elizaveta Semenyakina, Ivan Snegirev, Mikhail Kiselev +4
Vision-language-action policies may predict a transferable manipulation strategy yet fail to realize it reliably on the encountered object: objects compatible with the same grasp d…
SocialVLA: A Social Perception Gateway for Human-Reaction-Based Failure Detection and Recovery in VLA Manipulation
Sofya Konstantinova, Miguel Altamirano Cabrera, Artem Lykov +1
Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors. Human observers provide complementary…
CognitiveReality: Robot-Agnostic Semantic Gaussian Mapping with an LLM Agent for Immersive Collaborative VR Teleoperation
Timofei Kozlov, Dmitrii Maliukov, Andrey Marchenko +3
A photorealistic 3D view tells a teleoperator where a robot is, but not what the scene contains, how well each object has been observed, or how to turn pointing and speech into rob…
Kintsugi-VLA: Turning Failed Robot Rollouts into Recovery Data through Interventional Recoverability
Ivan Snegirev, Elizaveta Semenyakina, Dmitrii Maliukov +2
Simulation enables scalable training of Vision-Language-Action policies by using privileged experts to generate visual demonstrations without requiring every trajectory to be colle…
FlockDiffusion: Assignment-Conditioned Diffusion for Multi-Drone Task Allocation and Completion
Iana Zhura, Satenik Akopyan, Roohan Ahmed Khan +3
Autonomous multi-drone navigation requires fleets to service distributed objectives in cluttered environments under tight computational budgets. Efficient coordination depends on t…
AcousticDiffusion: Semantically Conditioned Audio-Guided Diffusion Policy for Search-and-Rescue Assistance
Iana Zhura, Didar Seyidov, Dmitrii Plotnikov +3
Navigating toward human callers is an important capability for rescue robots operating where visual contact is degraded or occluded. We present AcousticDiffusion, a semantically co…
ZeroTouch: Tactile-Supervised Visual Contact Estimation for Contact-Rich Manipulation
Dmitriy Kosenkov, Daniia Zinniatullina, Miguel Altamirano Cabrera +3
Reliable robotic grasping benefits from estimating the evolving physical interaction and selecting a grasp-dependent compression target. Tactile sensors provide direct interaction…
GaussAnything: Semantic Intent-Driven Refinement of Evolving Gaussian Scenes for Standalone VR
Dmitrii Maliukov, Timofei Kozlov, Dmitrii Plotnikov +2
Deploying reconstructed 3D environments on standalone VR headsets are constrained by limited compute and memory, and conventional level-of-detail policies optimize for visibility w…
UltraArUco: A Lightweight Multilingual Library And Framework With Low-Latency Real-Time Marker-Based Tracking System For Mobile AR Interaction
Mikhail Kiselev, Aleksandr Marukhin, Ivan Snegirev +3
UltraArUco is a lightweight multilingual library and framework for low latency, realtime marker-based tracking in mobile augmented reality. Unlike standard OpenCV-based implementat…
GeminiPainter's sequence-formed pipeline comprised of perception, cognition, planning, and action stages
Miguel Altamirano Cabrera, Aleksey Fedoseev, Iana Zhura +1
We present an autonomous robotic portrait-generation system combining real-time face detection, AI-based sketch generation, and robotic drawing. The system captures video frames, e…
SpaceVLA: Spatially Grounded VLA for Robotic Manipulation with User-Authored Grasp and Place Anchors
Daniia Zinniatullina, Iaroslav Kolomiets, Mikhail Konenkov +2
Vision-language-action (VLA) models follow language commands but often lack explicit spatial intent for manipulation. We present Visual Intent Anchors, an XR pipeline that lets use…
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…
OmniAI: A Surface-Adaptive Aerial Projection Interface for Human--Drone Interaction
Nikita Kuzmin, Yuhua Jin, Georgii Demianchuk +6
Drones in human environments often lack spatially grounded in- terfaces for situated communication. We present OmniAI, an em- bodied aerial agent that supports surface-adaptive int…
AnythingReality: Robust Online Gaussian Splatting SLAM for Open-Vocabulary VR Scene Exploration
Timofei Kozlov, Dmitrii Maliukov, Andrey Marchenko +2
We present a novel integrated architecture for robust online 3D Gaussian splatting, real-time VR exploration, and speech-driven Vision-Language-Model interaction. Unlike methods as…
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…
AnyGoal: Vision-Language Guided Multi-Agent Exploration for Training-Free Lifelong Navigation
MoniJesu James, Marcelino Julio Fernando, Miguel Altamirano Cabrera +1
End-to-end navigation policies trained on large simulation corpora degrade sharply when transferred to out-of-distribution scenes, categories, or goal modalities. Modular pipelines…
Action Agent: Agentic Video Generation Meets Flow-Constrained Diffusion
Jeffrin Sam, Nguyen Khang, Yara Mahmoud +2
We present Action Agent, a two-stage framework that unifies agentic navigation video generation with flow-constrained diffusion control for multi-embodiment robot navigation. In St…
GraspSense: Physically Grounded Grasp and Grip Planning for a Dexterous Robotic Hand via Language-Guided Perception and Force Maps
Elizaveta Semenyakina, Ivan Snegirev, Mariya Lezina +3
Dexterous robotic manipulation requires more than geometrically valid grasps: it demands physically grounded contact strategies that account for the spatially non-uniform mechanica…
GenerativeMPC: VLM-RAG-guided Whole-Body MPC with Virtual Impedance for Bimanual Mobile Manipulation
Marcelino Julio Fernando, Miguel Altamirano Cabrera, Jeffrin Sam +3
Bimanual mobile manipulation requires a seamless integration between high-level semantic reasoning and safe, compliant physical interaction - a challenge that end-to-end models app…
DiffusionAnything: End-to-End In-context Diffusion Learning for Unified Navigation and Pre-Grasp Motion
Iana Zhura, Yara Mahmoud, Jeffrin Sam +4
Efficiently predicting motion plans directly from vision remains a fundamental challenge in robotics, where planning typically requires explicit goal specification and task-specifi…
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…
Hybrid F' and ROS2 Architecture for Vision-Based Autonomous Flight: Design and Experimental Validation
Abdelrahman Metwally, Monijesu James, Aleksey Fedoseev +3
Autonomous aerospace systems require architectures that balance deterministic real-time control with advanced perception capabilities. This paper presents an integrated system comb…
GuideTouch: An Obstacle Avoidance Device with Tactile Feedback for Visually Impaired
Timofei Kozlov, Artem Trandofilov, Georgii Gazaryan +3
Safe navigation for the visually impaired individuals remains a critical challenge, especially concerning head-level obstacles, which traditional mobility aids often fail to detect…