VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots
Srivastava, Kushagra, Kulkarni, Rutwik, Velmurugan, Manoj, Sanket, Nitin J.
–arXiv.org Artificial Intelligence
All the images in this paper are best viewed in color on a computer screen at 200% zoom. Abstract -- Autonomous aerial robots are becoming commonplace in our lives. Hands-on aerial robotics courses are pivotal in training the next-generation workforce to meet the growing market demands. Such an efficient and compelling course depends on a reliable testbed. We utilize pose from an external localization system to hallucinate real-time and photorealistic visual sensors using 3D Gaussian Splatting. This enables stress-free testing of autonomy algorithms on aerial robots without the risk of crashing into obstacles. We achieve over 100Hz of system update rate. Lastly, we build upon our past experiences of offering hands-on aerial robotics courses and propose a new open-source and open-hardware curriculum based on VizFlyt for the future. We test our framework on various course projects in real-world HITL experiments and present the results showing the efficacy of such a system and its large potential use cases. Code, datasets, hardware guides and demo videos are available at https://pear .wpi.edu/research/vizflyt.html
arXiv.org Artificial Intelligence
Apr-1-2025
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