Telemanipulation systems - in 1925 a vision to remotelytreat patients, today widely adopted in a variety of applications - allow humanoperators to perform tasks which otherwise could not be performed, due to, forexample, limitations with respect to distance (e.g., space), scale (e.g.,surgery or micro-assembly) or hostile environments (e.g., subsea, nuclear).Effectively, a telemanipulation system functions as an extension to the humanoperator’s motor apparatus, in which the mapping between motor commands andhuman hand is shifted to a mapping between motor commands and slave robot.Haptic feedback, both proprioceptive and tactile, is often essential for motorcontrol and motor learning (i.e., building the `mappings'), but may bedistorted or even lost when not appropriately re-engineered.  There is, however, no consensus on how todesign haptic feedback to best enable humans to perform practicaltelemanipulated tasks, as no theory or integrated view for human-in-the-loopdesign and evaluation of haptic feedback is available. Empirically, we knowdesign guidelines `depend’ on aspects such as operator talent, training, thetype of task or application, quality of the visual feedback, or taskinstruction. As a result, the design and evaluation of a telemanipulationsystem is heuristic: for each case, the required quality of haptic feedback isdetermined by trial-and-error. This lacuna in design guidelines based onhuman-in-the-loop theory makes telemanipulation performance suboptimal, anddevelopment slow and costly.   The aim ofthis thesis is to provide an integrated, human-centered view on the design andevaluation of haptic feedback, which can serve as a basis for generalizedhaptic feedback design. More specifically, this thesis is on the one handfocused on (i) assessment of haptic feedback design requirements for positionand rate control within a uniform evaluation framework, and on the other on(ii) the development of a fundamental understanding of the role of hapticfeedback on operator (neuromuscular) control mechanisms, and moreover, togeneralize experimental findings by adapting existing motor-control paradigmsand control-theoretic models. To do so, four key human-factor experiments wereperformed. The first experiment focused on the benefit of haptic feedback forposition controlled telemanipulation scenarios and the impact of taskinstruction and availability of visual feedback for several fundamentalsubtasks. In a second experiment the efficacy of four different haptic feedbackinterface designs for rate control was determined in a similar manner; bothstudies adopted a uniform evaluation framework, providing an integrated view onrequirements for the haptic feedback.  Wefound that such a framework should incorporate at least a (abstract) tasktaxonomy, a baseline to compare against, task instruction, speed-accuracytrade-offs (i.e. what metrics to look at), performance-control efforttrade-offs, operator training, and a control on the quality of visual feedback.Furthermore, these studies showed that the best haptic feedback design toperform a given telemanipulation task predominantly depends on the requiredtask workspace and task accuracy, and the need to reflect back contacttransitions. Large workspaces are more easily (i.e. low workload) covered usingrate control, where accuracy for positions and forces is higher using positioncontrol. Also, as an increase in device (i.e. haptic feedback) quality does notalways correlate to an increase in task performance. This implies design ofhaptic feedback should be human-centered evaluation, both assessing the problemand validating the solution with the human in-the-loop. Experiments three andfour focused on the effects of haptic feedback on the human operator’s motorcontrol mechanisms when controlling a telemanipulation system in free-space. Instudy three, well-established cybernetic models were adopted to study trainedmovements, and the impact of slave dynamics and scaling of haptic feedback. Inthe final study, a reach-adaptation paradigm was used to study the role ofhaptic feedback when learning movements, and the impact of slave dynamics and bandwidthof the presented haptic feedback.  Theselatter two experiments show that haptic feedback substantially affects anoperator’s underlying motor control mechanisms (i.e. feedback and feedforwardcontrol) when controlling a slave system. The effects were observed in bothinstantaneous improvements of task execution due to feedback of environmentalforces or device dynamics, as well as also task execution improvements overlonger periods of time due to improved internal models (i.e. learning); hapticfeedback enhances the process of building ‘mappings’ between human input and asystem’s response. This suggests that improved haptic feedback quality improveslearning rates (i.e. efficacy) and control responses (i.e. efficiency). Futurestudies should uncover the potential quantitative effects and time-scales atwhich these effects occur.  Additionally,study three showed that the amplitude of haptic feedback can be scaled downwithout harming task performance: human operators are capable of adjustingtheir (neuromuscular) control parameters independently of the absolutemagnitude (i.e. gain) of the haptic feedback controller. However, when scaling,one should account for reasonable lower boundaries, that putatively may begiven by Just Noticeable Differences (JNDs) to keep cues distinguishable. Upperboundaries may be given by individual constraints on comfort. These findingswere confirmed by the second experiment.  Studies three and four illustrate thatcomputational models and paradigms from the motor control literature can beadopted to provide generalizable descriptions of human operator behavior intelemanipulation. Here, we targeted free-space motions for systems like cranesand robot arms, and the tasks are representative for activities in domestic,nuclear or subsea environments. The cybernetic models enable for an exclusiveunderstanding of the underlying operator control mechanisms (i.e. feedback andfeedforward control) by looking in the frequency domain, as such complementingand enhancing the insights gained from the time-domain data. The reachadaptation paradigm enables to determine the extent to which haptic feedbackbandwidth affects motor learning and generalization for different slavedynamics. Moreover, these model-based approaches enable extrapolation offindings and to predict outcomes when task characteristics change, such thatinformed a priori design considerations of haptic feedback interfaces and, inthe future, haptic support systems can be made.

For the planned teleoperated maintenance of the experimental fusion plant ITER the time performance will be critical. Telemanipulated task execution is however characterised by long execution times compared to similar tasks performed hands-on. There is little quantitative research on task performance of telemanipulated maintenance available to give insight into most effective areas for improvement.In this paper a detailed analysis of real world remote maintenance at fusion plant JET is performed with the aim to: i) identify bottlenecks in task completion time and ii) quantify the room for potential improvement.Video recordings of the installation of 50 tiles executed by the three official master-slave operators were analysed. The task execution was characterised by a large variation in time performance, between but also within operators. Reduction of this variation could theoretically result in time reduction up to 41%. Recurring tasks like 'rough/fine approach' and 'retreat' covered more than 50% of the total task completion time and were identified as most promising for further improvement.The results will be the base for further research on operator assistance with augmented visual or haptic guidance.

Telemanipulation techniques allow for human-in-the-loop assembly and maintenance tasks in otherwise inaccessible environments. Although it comes with limitations in achieved performance - required strict operator selection and extensive training are widely encountered - there is very little quantitative insight in the exact problems operators encounter during task execution. This paper provides a novel hierarchical task analysis approach to identify the most time-consuming subtask elements and to quantify the potential room for performance improvement during telemanipulated maintenance tasks. The approach is illustrated with a human factors case study in which 5 subjects performed six generic maintenance tasks, using a six degree of freedom master device connected to a simulated task environment. Overall it can be concluded that the proposed three phased task analysis is a useful tool to guide improvements since it is able to relate high-level problems (e.g. large variability) to behaviour on lower task-levels. For the case study, the largest potential for improvement was found for specific subtasks characterized by complex contact transitions and precise control of tool orientation, and in the reduction of variation of the task execution.