This paper reports on a Field Experiment carried out by the Human Research and Engineering Directorate at Ft. Benning
to evaluate the efficacy of using speech to control an Unmanned Ground Vehicle (UGV) concurrently with a handcontroller.
The SPEAR system, developed by Think-A-Move, provides speech-control of UGVs. The system picks up
user-speech in the ear canal with an in-ear microphone. This property allows it to work efficiently in high-noise
environments, where traditional speech systems, employing external microphones, fail. It has been integrated with an
iRobot PackBot 510 with EOD kit. The integrated system allows the hand-controller to be supplemented with speech for
concurrent control. At Ft. Benning, the integrated system was tested by soldiers from the Officer Candidate School. The
Experiment had dual focus: 1) Quantitative measurement of the time taken to complete each station and the cognitive
load on users; 2) Qualitative evaluation of ease-of-use and ergonomics through soldier-feedback. Also of significant
benefit to Think-A-Move was soldier-feedback on the speech-command vocabulary employed: What spoken commands
are intuitive, and how the commands should be executed, e.g., limited-motion vs. unlimited-motion commands. Overall
results from the Experiment are reported in the paper.
Hands-free control of unmanned ground vehicles is essential for soldiers, bomb disposal squads, and first responders.
Having their hands free for other equipment and tasks allows them to be safer and more mobile. Currently, the most
successful hands-free control devices are speech-command based. However, these devices use external microphones,
and in field environments, e.g., war zones and fire sites, their performance suffers because of loud ambient noise:
typically above 90dBA. This paper describes the development of technology using the ear as an output source that can
provide excellent command recognition accuracy even in noisy environments. Instead of picking up speech radiating
from the mouth, this technology detects speech transmitted internally through the ear canal. Discreet tongue movements
also create air pressure changes within the ear canal, and can be used for stealth control. A patented earpiece was
developed with a microphone pointed into the ear canal that captures these signals generated by tongue movements and
speech. The signals are transmitted from the earpiece to an Ultra-Mobile Personal Computer (UMPC) through a wired
connection. The UMPC processes the signals and utilizes them for device control. The processing can include command
recognition, ambient noise cancellation, acoustic echo cancellation, and speech equalization. Successful control of an
iRobot PackBot has been demonstrated with both speech (13 discrete commands) and tongue (5 discrete commands)
signals. In preliminary tests, command recognition accuracy was 95% with speech control and 85% with tongue control.