ICUAS'23 Paper Abstract

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Paper ThB1.4

Arora, Prateek (University of Nevada - Reno), Karakurt, Tolga (University of Nevada - Reno), Avloniti, Eleni Spyridoula (University of Thessaly), Carlson, Stephen (University of Nevada - Reno), Moore, Brandon (University of Nevada - Reno), Feil-Seifer, David (University of Nevada - Reno), Papachristos, Christos (University of Nevada - Reno)

Deep Learning-Based Reassembling of an Aerial & Legged Marsupial Robotic System-Of-Systems

Scheduled for presentation during the Regular Session "Current Advances in UAS – Best Paper Finalists" (ThB1), Thursday, June 8, 2023, 12:00−12:20, Room 118

2023 International Conference on Unmanned Aircraft Systems (ICUAS), June 6-9, 2023, Lazarski University, Warsaw, Poland

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Micro- and Mini- UAS, Autonomy, Perception and Cognition

Abstract

In this work we address the System-of-Systems reassembling operation of a marsupial team comprising a hybrid Unmanned Aerial Vehicle and a Legged Locomotion robot, relying solely on vision-based systems and assisted by Deep Learning. The target application domain is that of large-scale field surveying operations under the presence of wireless communication disruptions. While most real-world field deployments of multi-robot systems assume some degree of wireless communication to coordinate key tasks such as multi-agent rendezvous, a desirable feature against unrecoverable communication failures or radio degradation due to jamming cyber-attacks is the ability for autonomous systems to robustly execute their mission with onboard perception. This is especially true for marsupial air / ground teams, wherein landing onboard the ground robot is required. We propose a pipeline that relies on Deep Neural Network-based Vehicle-to-Vehicle detection based on aerial views acquired by flying at typical altitudes for Micro Aerial Vehicle-based real-world surveying operations, such as near the border of the 400ft Above Ground Level window. We present the minimal computing and sensing suite that supports its execution onboard a fully autonomous micro-Tiltrotor aircraft which detects, approaches, and lands onboard a Boston Dynamics Spot legged robot. We present extensive experimental studies that validate this marsupial aerial / ground robot's capacity to safely reassemble while in the airborne scouting phase without the need for wireless communication.

 

 

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