47 citations · 255 across the 195 of their papers we have counts for
179 papers · 1 filter
ReForesight: Occlusion-Robust Re-Identification and Future Occupancy Forecasting for Dynamic Semantic Mapping
Didar Seyidov, Faith Ogunwoye, Hajira Amjad +3
Robots sharing walkways need to know where people will be, yet semantic occupancy maps show only where they are. We present ReForesight, an open-source ROS 2 toolkit that adds inst…
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…
HapticWAM: Distilling Imagined Touch into a World-Action Model without Inference-Time Tactile Sensing
Mikhail Sannikov, Ilya Mikhalchuk, Konstantin Gubernatorov +3
Contact-rich manipulation requires estimating forces, slip and contact geometry that can remain ambiguous in scene images. Optical tactile sensors provide both visual observations…
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…
AgenticSwarm: Semantic Perception and Adaptive Task Allocation for Heterogeneous Multi-UAV Missions
Muhammad Ahsan Mustafa, Yasheerah Yaqoot, Faryal Batool +3
Multi UAV missions in complex environments require the system to understand both the surrounding scene and the intent of a human operator while maintaining feasible task allocation…
SmellDiffusion: Diffusion-Based Quadruped Navigation with Olfactory Scene Graphs
Faith Ogunwoye, Iana Zhura, Hajira Amjad +5
A robot sent to a named gas leak must preserve gas identity, estimate the source, and navigate to the resulting goal. We present SmellDiffusion, a simulation pipeline that represen…
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…
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…
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…
DIFF-IPPO: Diffusion-Based Informative Path Planning with Open-Vocabulary Belief Maps
Sausar Karaf, Oleg Sautenkov, Mikhail Martynov +1
Exploration and object search require robots to perceive their environment, identify regions of interest, and plan trajectories that improve target-detection likelihood or maximize…
Guided Diffusion with Distilled Vision-Language Reliability for Aerial Navigation
Ivan Valuev, Iana Zhura, Valerii Serpiva +2
Autonomous UAV navigation is conventionally solved by pipelines that separate perception, mapping, and planning into distinct stages, which propagates errors, accumulates latency,…
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…
AgenticRL: Agentic Reinforcement Learning with Self-Refinement for Complex UAV Navigation
Roohan Ahmed Khan, Yasheerah Yaqoot, Amir Atef Habel +2
Deep reinforcement learning enables autonomous robots to learn complex navigation tasks, but still relies heavily on time consuming manual reward design and fine tuning. Existing a…
AgenticDiffusion: Multi-View Reasoning with View-Conditioned Diffusion Planning for Vision-Based UAV Navigation
Faryal Batool, Muhammad Ahsan Mustafa, Fawad Mehboob +2
Vision-based UAV navigation becomes challenging when navigation targets are distributed across complementary camera views and cannot be reliably observed from a single viewpoint. W…
Output-Level Regularization Eliminates the Seed Lottery in Single-GPU VLA Fine-Tuning
Jeffrin Sam, Dzmitry Tsetserukou
Fine-tuning a vision-language-action model (VLA-JEPA) on a single GPU should be simple: load a pretrained checkpoint, run training, deploy. There is a hidden danger. Run the same f…
GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment
Ziang Guo, Chen Min, Xuefeng Zhang +5
End-to-end (E2E) autonomous driving aims to directly map sensory observations to driving actions, but its real-world deployment is hindered by evolving data distributions and the h…
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…