A Perceptual Computing based Gesture Controlled Quadcopter for Visual Tracking and Transportation

A Perceptual Computing based Gesture Controlled Quadcopter for Visual Tracking and Transportation

Kumar Yelamarthi (Central Michigan University, Mt Pleasant, MI, USA), Raghudeep Kannavara (Intel Corporation, Hillsboro, OR, USA) and Sanjay Boddhu (Finch Computing, Dayton, OH, USA)
DOI: 10.4018/IJMSTR.2015040104
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Abstract

One of the fundamental challenges faced by an inexperienced user in portable unmanned aerial vehicle (UAV) such as quadcopters is flight control, often leading to crashes. Addressing this challenge, and leveraging upon the technological advancement in perceptual computing and computer vision, this research presents a modular system that allows for hand gesture based flight control of UAV, alongside a transport mechanism for portable objects. In addition to ascertain smooth flight control by avoiding obstacles in navigation path, real-time video feedback is relayed from the UAV to user, thus allowing him/her to take appropriate actions. This paper presents the design implementation by discussing the various sub-systems involved, inter system communication, and field tests to ascertain operation. As presented from testing results, the proposed system provides efficient communication between the subsystems for smooth flight control, while allowing for safe transport of portable objects.
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2. Previous Work

Perceptual computing is a new technology that is in its early stages of development. There are some consumer products that utilize this technology. The most prevalent and well known of these devices is Microsoft’s Kinect sensor for the Xbox 360 (Kinect, 2015). This device is used as a game controller and interprets the user’s large motion gestures, i.e. arm swinging and bending of the limbs, and is also used for localization of objects (Yelamarthi, DeJong, & Laubhan, 2014). This project is intended for use in a setting that requires more discrete gestures. The Microsoft Kinect is not designed to perceive gestures as small as the ones the user will input to the system. The Creative Labs Senz3D camera is fully capable of providing the desired perceptual computing for interpreting the discrete gestures (Creative, 2014).

In terms of item retrieval and delivery, aerial transportation systems using quad-copters are gaining popularity in today’s tech world. Transportation systems like the Matternet are constrained by concepts such as aerial transportation and poor controllability (D'Andrea, 2014). Systems with fully integrated gesture control that are currently in use today are scarce. One such system consisted of an obstacle avoiding wheelchair that used the user’s head gestures for control (Jia, 2007), as developed for elderly and disabled humans.

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