Intuitive Human-Drone Collaborative Navigation in Unknown Environments through Mixed Reality
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arXiv
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| Format: | Preprint |
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2025
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| author | Salunkhe, Sanket A. Nedunghat, Pranav Morando, Luca Bobbili, Nishanth Li, Guanrui Loianno, Giuseppe |
| author_facet | Salunkhe, Sanket A. Nedunghat, Pranav Morando, Luca Bobbili, Nishanth Li, Guanrui Loianno, Giuseppe |
| contents | Considering the widespread integration of aerial robots in inspection, search and rescue, and monitoring tasks, there is a growing demand to design intuitive human-drone interfaces. These aim to streamline and enhance the user interaction and collaboration process during drone navigation, ultimately expediting mission success and accommodating users' inputs. In this paper, we present a novel human-drone mixed reality interface that aims to (a) increase human-drone spatial awareness by sharing relevant spatial information and representations between the human equipped with a Head Mounted Display (HMD) and the robot and (b) enable safer and intuitive human-drone interactive and collaborative navigation in unknown environments beyond the simple command and control or teleoperation paradigm. We validate our framework through extensive user studies and experiments in a simulated post-disaster scenario, comparing its performance against a traditional First-Person View (FPV) control systems. Furthermore, multiple tests on several users underscore the advantages of the proposed solution, which offers intuitive and natural interaction with the system. This demonstrates the solution's ability to assist humans during a drone navigation mission, ensuring its safe and effective execution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_01350 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Intuitive Human-Drone Collaborative Navigation in Unknown Environments through Mixed Reality Salunkhe, Sanket A. Nedunghat, Pranav Morando, Luca Bobbili, Nishanth Li, Guanrui Loianno, Giuseppe Robotics Considering the widespread integration of aerial robots in inspection, search and rescue, and monitoring tasks, there is a growing demand to design intuitive human-drone interfaces. These aim to streamline and enhance the user interaction and collaboration process during drone navigation, ultimately expediting mission success and accommodating users' inputs. In this paper, we present a novel human-drone mixed reality interface that aims to (a) increase human-drone spatial awareness by sharing relevant spatial information and representations between the human equipped with a Head Mounted Display (HMD) and the robot and (b) enable safer and intuitive human-drone interactive and collaborative navigation in unknown environments beyond the simple command and control or teleoperation paradigm. We validate our framework through extensive user studies and experiments in a simulated post-disaster scenario, comparing its performance against a traditional First-Person View (FPV) control systems. Furthermore, multiple tests on several users underscore the advantages of the proposed solution, which offers intuitive and natural interaction with the system. This demonstrates the solution's ability to assist humans during a drone navigation mission, ensuring its safe and effective execution. |
| title | Intuitive Human-Drone Collaborative Navigation in Unknown Environments through Mixed Reality |
| topic | Robotics |
| url | https://arxiv.org/abs/2504.01350 |