H. Boessenkool

The Impact of Haptic Feedback Quality on the Performance of Teleoperated Assembly Tasks

In teleoperation, haptic feedback allows the human operator to touch the remote environment. Yet, it is only partially understood to what extent the quality of haptic feedback contributes to human-in-the-loop task performance. This paper presents a human factors experiment in which teleoperated task performance and control effort are assessed for a typical (dis-)assembly task in a hard-to-hard environment, well known to the operator. Subjects are provided with four levels of haptic feedback quality: no haptic feedback, low-frequency haptic feedback, combined low- and high-frequency haptic feedback, and the best possible-a natural spectrum of haptic feedback in a direct-controlled equivalent of the task. Four generalized fundamental subtasks are identified, namely: 1) free-space movement, 2) contact transition, 3) constrained translational, and 4) constrained rotational tasks. The results show that overall task performance and control effort are primarily improved by providing low-frequency haptic feedback (specifically by improvements in constrained translational and constrained rotational tasks), while further haptic feedback quality improvements yield only marginal performance increases and control effort decreases, even if a full natural spectrum of haptic feedback is provided.

A Task-Specific Analysis of the Benefit of Haptic Shared Control During Telemanipulation

Telemanipulation allows human to perform operations in a remote environment, but performance and required time of tasks is negatively influenced when (haptic) feedback is limited. Improvement of transparency (reflected forces) is an important focus in literature, but despite significant progress, it is still imperfect, with many unresolved issues. An alternative approach to improve teleoperated tasks is presented in this study: Offering haptic shared control in which the operator is assisted by guiding forces applied at the master device. It is hypothesized that continuous intuitive interaction between operator and support system will improve required time and accuracy with less control effort, even for imperfect transparency. An experimental study was performed in a hard-contact task environment. The subjects were aided by the designed shared control to perform a simple bolt-spanner task using a planar three degree of freedom (DOF) teleoperator. Haptic shared control was compared to normal operation for three levels of transparency. The experimental results showed that haptic shared control improves task performance, control effort and operator cognitive workload for the overall bolt-spanner task, for all three transparency levels. Analyses per subtask showed that free air movement (FAM) benefits most from shared control in terms of time performance, and also shows improved accuracy.

The Effect of Trial-by-Trial Adaptation on Conflicts in Haptic Shared Control for Free-Air Teleoperation Tasks

Haptic shared control can improve execution of teleoperation and driving tasks. However, shared control designs may suffer from conflicts between individual human operators and constant haptic assistance when their desired trajectories differ, leading to momentarily increased forces, discomfort, or even deteriorated performance. This study investigates ways to reduce conflicts between individual human operators and a haptic shared controller by modifying supported trajectories. Subjects (n=12) performed a repetitive movement task in an abstract environment with varying spatio-temporal constraints, both during manual control and while supported by haptic shared control. Four types of haptic shared control were compared, combining two design properties: the initial supported trajectory (either the centerline of the environment or an individualized trajectory based on manual control trials), and trial-by-trial adaptation of guidance towards previously performed trajectories (either present or absent). Trial-by-trial adaptation of guidance reduced conflicts compared to non-adaptive guidance, whether the initial trajectory was individualized or not. Without trial-by-trial adaptation, individualized trajectories also reduced conflicts, but not completely: when guided, operators adapt their preferred trajectories. In conclusion, trial-by-trial adaptation is the most promising approach to mitigate conflicts during repetitive motion tasks.