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

Abstract

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.

Decision-Making Model for Adaptive Impedance Control of Teleoperation Systems

“…In telerobotics, Boessenkool et.al [24] reported that haptic assistance improves task performance compared to noassistance in a structured environment; in our case a similar result is obtained but extended to a partially structured environment.…”

“…The benefits of having varying assistance schemes over constant schemes (or non-assisted configurations) are explored in [1], [5], [16], [24]. They conclude that incorporating assistance improves task performance compared to no assistance, but this is only true when the human operator agrees with the proposed assistance strategy.…”

“…This generic scenario underlies a series of reallife teleoperation applications (e.g. [18], [24]), but also other scenarios in physical human-robot interaction (consider e.g. a mobility assistant [36], human-robot collaborative manipulation [15], [16], rehabilitation [37]) or training with a haptic aid [38].…”

Evaluation of Haptic and Visual Cues for Repulsive or Attractive Guidance in Nonholonomic Steering Tasks

“…This concept essentially acts as a second controller and is known as haptic shared control [20], [21]. It has been applied to car driving [20]- [23], subsea robotics [24], teleoperated surgery [25], and nuclear maintenance [26].…”

Shared-control for the kinematic model of a mobile robot

“…The present paper proposes a shared-control method to drive a wheeled mobile robot in the case in which the control authority is shared by a human operator and a feedback controller. This shared-control system is widely used in the modern world, for example in intelligent wheelchairs [7], teleoperations [8], transportations [9] and medicine [10]. The paper [11] has shown that there are four types of robot modes according to the level of system's autonomy and has demonstrated that collaborative control can increase performance and reduce error compared with manual operation, whereas [12] has introduced the idea of task-level adaptive shared-control to assembly systems and demonstrated that the resulting system is flexible and able to accomodate changes.…”