Teleoperated mobile robots, equipped with object manipulation capabilities, provide safe means for executing dangerous tasks in hazardous environments without putting humans at risk. However, mainly due to a communication delay, complex operator interfaces and insufficient Situational Awareness (SA), the task productivity of telerobots remains inferior to human workers. This paper addresses the shortcomings of telerobots by proposing a combined approach of (i) a scalable and intuitive operator interface with gestural and verbal input, (ii) improved Situational Awareness (SA) through sensor fusion according to documented best practices, (iii) integrated virtual fixtures for task simplification and minimizing the operator’s cognitive burden and (iv) integrated semiautonomous behaviors that further reduce cognitive burden and negate the impact of communication delays, execution latency and/or failures. The proposed teleoperation system, TeMoto, is implemented using ROS (Robot Operating System) to ensure hardware agnosticism, extensibility and community access. The operator’s command interface consists of a Leap Motion Controller for hand tracking, Griffin PowerMate USB as turn knob for scaling and a microphone for speech input. TeMoto is evaluated on multiple robots including two mobile manipulator platforms. In addition to standard, task-specific evaluation techniques (completion time, user studies, number of steps, etc.)—which are platform and task dependent and thus difficult to scale—this paper presents additional metrics for evaluating the user interface including task-independent criteria for measuring generalized (i) task completion efficiency and (ii) operator context switching.
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