%0 Journal Article
%T Collaborative Exploration with a Micro Aerial Vehicle: A Novel Interaction Method for Controlling a MAV with a Hand-Held Device
%A David Pitman
%A Mary L. Cummings
%J Advances in Human-Computer Interaction
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/768180
%X In order to collaboratively explore an environment with a Micro Aerial Vehicle (MAV), an operator needs a mobile interface, which can support the operator¡¯s divided attention. To this end, we developed the Micro Aerial Vehicle Exploration of an Unknown Environment (MAV-VUE) interface, which allows operators with minimal training the ability to remotely explore their environment with a MAV. MAV-VUE employs a concept we term Perceived First-Order (PFO) control, which allows an operator to effectively ¡°fly¡± a MAV with no risk to the vehicle. PFO control utilizes a position feedback control loop to fly the MAV while presenting rate feedback to the operator. A usability study was conducted to evaluate MAV-VUE. This interface was connected remotely to an actual MAV to explore a GPS-simulated urban environment. 1. Introduction Field personnel, such as emergency first responders, police, specialists (e.g., building inspectors or bomb technicians), or dismounted, forward-deployed soldiers, often rely on satellite-based maps to gain information prior to or during field operations. All of these groups operate in hazardous environments, which may contain hostile, armed people, unstable structures, or environmental disasters. Satellite maps, currently the standard for performing Intelligence, Surveillance and Reconnaissance (ISR) of an outdoor environment, have many inherent flaws. As a flat image, these maps give no elevation information, and often, due to shadows and shading, give false impressions of elevation. For example, while it can be safely assumed that roads approximate a level plane, the rest of an urban environment is often closer to a series of blocks of varying heights or depths with shadows cast by adjacent buildings. Building entrances and exits are hidden due to the birds-eye view of a satellite image, with little to no information about a building's exterior. Moreover, this imagery is often outdated or relevant only to the season in which the image was taken. Combined, these flaws often give field personnel a false mental model of their environment. Many of these flaws and dangers could be remedied by having field personnel operate a robot to locally explore and map their environment. Given the need of these personnel to simultaneously perform another primary task, such as looking out for snipers, an autonomous robot (i.e., an Unmanned Vehicle (UV)) would allow these groups to better perform ISR and improve their Situational Awareness (SA) in real time by reducing attention needed from operating the robot. However, performing an ISR mission aided
%U http://www.hindawi.com/journals/ahci/2012/768180/