Soldier experiments and assessments using SPEAR? speech control system for UGVs

摘要

This paper reports on a Soldier Experiment performed by the Army Research Lab's Human Research Engineering Directorate (HRED) Field Element located at the Maneuver Center of Excellence, Ft. Benning, and a Limited Use Assessment conducted by the Marine Corps Forces Pacific Command Experimentation Center (MEC) at Camp Pendleton evaluating the effectiveness of using speech commands to control an Unmanned Ground Vehicle.rnSPEAR?, developed by Think-A-Move, Ltd., provides speech control of UGVs. SPEAR detects user speech in the ear canal with an earpiece containing an in-ear microphone. The system design provides up to 30 dB of passive noise reduction, enabling it to work well in high-noise environments, where traditional speech systems, using external microphones, fail; it also utilizes a proprietary speech recognition engine. SPEAR has been integrated with iRobot's PackBot 510 with FasTac Kit, and with Multi-Robot Operator Control Unit (MOCU), developed by SPA WAR Systems Center Pacific. These integrated systems allow speech to supplement the hand-controller for multi-modal control of different UGV functions simultaneously.rnHRED's experiment measured the impact of SPEAR on reducing the cognitive load placed on UGV Operators and the time to complete specific tasks. Army NCOs and Officer School Candidates participated in this experiment, which found that speech control was faster than manual control to complete tasks requiring menu navigation, as well as reducing the cognitive load on UGV Operators.rnThe MEC assessment examined speech commands used for two different missions: Route Clearance and Cordon and Search; participants included Explosive Ordnance Disposal Technicians and Combat Engineers. The majority of the Marines thought it was easier to complete the mission scenarios with SPEAR than with only using manual controls, and that using SPEAR improved their situational awareness.rnOverall results of these Assessments are reported in the paper, along with possible applications to autonomous mine detection systems.