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- Title
Autonomous Human-Vehicle Leader-Follower Control Using Deep-Learning-Driven Gesture Recognition.
- Authors
Schulte, Joseph; Kocherovsky, Mark; Paul, Nicholas; Pleune, Mitchell; Chung, Chan-Jin
- Abstract
Leader-follower autonomy (LFA) systems have so far only focused on vehicles following other vehicles. Though there have been several decades of research into this topic, there has not yet been any work on human-vehicle leader-follower systems in the known literature. We present a system in which an autonomous vehicle—our ACTor 1 platform—can follow a human leader who controls the vehicle through hand-and-body gestures. We successfully developed a modular pipeline that uses artificial intelligence/deep learning to recognize hand-and-body gestures from a user in view of the vehicle's camera and translate those gestures into physical action by the vehicle. We demonstrate our work using our ACTor 1 platform, a modified Polaris Gem 2. Results show that our modular pipeline design reliably recognizes human body language and translates the body language into LFA commands in real time. This work has numerous applications such as material transport in industrial contexts.
- Subjects
GESTURE; BODY language; AUTONOMOUS vehicles; TRANSLATING &; interpreting; DEEP learning; ARTIFICIAL intelligence; MODULAR design
- Publication
Vehicles (2624-8921), 2022, Vol 4, Issue 1, p243
- ISSN
2624-8921
- Publication type
Article
- DOI
10.3390/vehicles4010016