Flying Together: Human-Guided Immersive Shared Control for Aerial Robot Teams in Unknown Environments
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arXiv
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| Format: | Preprint |
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2026
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| author | De Bel-Air, Lou Morando, Luca Chen, Ruitao Wang, Keru Jarvis, Benjamin Toumieh, Charbel Zhou, Yang Perlin, Ken Floreano, Dario Loianno, Giuseppe |
| author_facet | De Bel-Air, Lou Morando, Luca Chen, Ruitao Wang, Keru Jarvis, Benjamin Toumieh, Charbel Zhou, Yang Perlin, Ken Floreano, Dario Loianno, Giuseppe |
| contents | While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator-driven objectives in unstructured environments. We present a Virtual Reality (VR)-based shared control framework for teams of drones operating in constrained and unknown environments, enabling real-time, user-guided exploration. At the core of our approach is a novel, user-guided motion-primitive-based planner that computes continuous, collision-free trajectories while continuously integrating operator input. This planner is coupled with an admittance controller, allowing the operator to flexibly influence team behavior and guide drones toward regions of interest that autonomous planners may overlook. The system supports mixed-reality operations with both physical and simulated drones, and implements a bilateral VR-based interface, allowing the operator to guide the robot team via migration points while receiving immediate visual feedback of the team state. Experimental results show that shared control improves obstacle avoidance, maintains inter-agent spacing, and reduces operator effort, demonstrating the feasibility and advantages of immersive, human-in-the-loop multi-robot navigation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_21680 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Flying Together: Human-Guided Immersive Shared Control for Aerial Robot Teams in Unknown Environments De Bel-Air, Lou Morando, Luca Chen, Ruitao Wang, Keru Jarvis, Benjamin Toumieh, Charbel Zhou, Yang Perlin, Ken Floreano, Dario Loianno, Giuseppe Robotics While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator-driven objectives in unstructured environments. We present a Virtual Reality (VR)-based shared control framework for teams of drones operating in constrained and unknown environments, enabling real-time, user-guided exploration. At the core of our approach is a novel, user-guided motion-primitive-based planner that computes continuous, collision-free trajectories while continuously integrating operator input. This planner is coupled with an admittance controller, allowing the operator to flexibly influence team behavior and guide drones toward regions of interest that autonomous planners may overlook. The system supports mixed-reality operations with both physical and simulated drones, and implements a bilateral VR-based interface, allowing the operator to guide the robot team via migration points while receiving immediate visual feedback of the team state. Experimental results show that shared control improves obstacle avoidance, maintains inter-agent spacing, and reduces operator effort, demonstrating the feasibility and advantages of immersive, human-in-the-loop multi-robot navigation. |
| title | Flying Together: Human-Guided Immersive Shared Control for Aerial Robot Teams in Unknown Environments |
| topic | Robotics |
| url | https://arxiv.org/abs/2605.21680 |