Scalability of Robotic Controllers: Speech-Based Robotic Controller Evaluation

摘要

This study, which took place at Fort Benning, GA, focused on the feasibility of reducing robotic controller size by replacing some of the manual controls with speech-based controls. Eleven Soldiers from the Officers Candidate School served as participants. After training on the operation of the iRobot PackBot small unmanned ground vehicle (SUGV) system, each Soldier teleoperated the SUGV using two controller conditions; a combination of speech and manual control and manual control only. Soldiers were tasked to drive the robot and to perform operations such as surveillance using the robotic arm. Controller type and usability were evaluated based on objective performance data, data collector observations, and Soldier questionnaire responses. Workload for each controller was measured by having the Soldiers complete the National Aeronautics and Space Administration Task Load Index survey after using each controller type. Speech-based control exhibited the potential for benefits beyond controller size reduction. It decreased time and effort when performing multiple tasks simultaneously by allowing speech commands to be given for control of the robotic arm while at the same time maneuvering the robot using manual controls. The speech-based control system also has the potential to provide other benefits beyond those addressed in this study.