Review of Teleoperator Research

A predictor display to overcome time lag problems with remote control systems is discussed. The video picture is a (necessarily) time-delayed picture from the remote location, generated as a coherent frame (snapshot) so that all picture elements in a single scan are delayed the same. The computer-generated graphics is a line drawing of the present configuration of the manipulator arm, vehicle or other device. The latter is generated by using the same control signals which are sent to the remote manipulator (device) to drive a computer model of it. The computer model is drawn on the video display in exactly the same location as where it will actually be after a one-way time delay and where it will be seen to be on the video after one round-trip time delay. If one waits at least one round-trip delay without moving, both the graphics model and the video picture of the manipulator (device) are seen to coincide. The predictor technque proved to work well and was shown for time delays in the 1-3 second range to reduce completion times for a variety of manipulation tasks by 50-150 percent reliably

MIT research in telerobotics

Ongoing MIT research in telerobotics (vehicles capable of some autonomous sensing and manipulating, having some remote supervisory control by people) and teleoperation (vehicles for sensing and manipulating which are fully controlled remotely by people) is discussed. The current efforts mix human and artificial intelligence/control. The idea of adjustable impedance at either end of pure master-slave teleoperation, and simultaneous coordinated control of teleoperator/telerobotic systems which have more than six degrees of freedom (e.g., a combined vehicle and arm, each with five or six DOF) are discussed. A new cable-controlled parallel link arm which offers many advantages over conventional arms for space is briefly described. Predictor displays to compensate for time delay in teleoperator loops, the use of state estimation to help human control decisions in space, and ongoing research in supervisory command language are covered. Finally, efforts to build a human flyable real-time dynamic computer-graphic telerobot simulator are described. These projects represent most, but not all, of the telerobotics research in our laboratory, supported by JPL, NASA Ames and NOAA

Video framerate, resolution and grayscale tradeoffs for undersea telemanipulator

The product of Frame Rate (F) in frames per second, Resolution (R) in total pixels and grayscale in bits (G) equals the transmission band rate in bits per second. Thus for a fixed channel capacity there are tradeoffs between F, R and G in the actual sampling of the picture for a particular manual control task in the present case remote undersea manipulation. A manipulator was used in the MASTER/SLAVE mode to study these tradeoffs. Images were systematically degraded from 28 frames per second, 128 x 128 pixels and 16 levels (4 bits) grayscale, with various FRG combinations constructed from a real-time digitized (charge-injection) video camera. It was found that frame rate, resolution and grayscale could be independently reduced without preventing the operator from accomplishing his/her task. Threshold points were found beyond which degradation would prevent any successful performance. A general conclusion is that a well trained operator can perform familiar remote manipulator tasks with a considerably degrade picture, down to 50 K bits/ sec

A model for dynamic allocation of human attention among multiple tasks

The problem of multi-task attention allocation with special reference to aircraft piloting is discussed with the experimental paradigm used to characterize this situation and the experimental results obtained in the first phase of the research. A qualitative description of an approach to mathematical modeling, and some results obtained with it are also presented to indicate what aspects of the model are most promising. Two appendices are given which (1) discuss the model in relation to graph theory and optimization and (2) specify the optimization algorithm of the model

Supervisory sampling and control: Sources of suboptimality in a prediction task

A process supervisor is defined as a person who decides when to sample the process input and what values of a control variable to specify in order to maximize (minimize) a given value function of input sampling period, control setting, and process state. Presented experimental data in such a process where the value function is a time-averaged sampling cost plus mean squared difference between input and control variable. The task was unpaced prediction of the output of a second order filter driven by white noise. Experimental results, when compared to the optical strategy, reveal several consistently suboptimal behaviors. One is a tendency not to choose a long prediction interval even though the optimal strategy dictates that one should. Some results are also interpreted in terms of those input parameters according to which each subjects' behavior would have been nearest optimal. Differences of those parameters from actual input parameters served to quantify how subjects' prediction behavior differed from optimal

Two-D results on human operator perception

The application of multidimensional scaling methodology in human factors engineering is presented. The nonorthogonality of internally perceived task variables is exhibited for first and second order plants with both dependent and independent task variables. Directions of operator preference are shown for actual performance, pilot opinion rating, and subjective measures of fatigue, adaptability, and system recognition. Improvement of performance in second order systems is exhibited by the use of bang-bang feedback information. Dissimilarity measures for system comparison are suggested in order to account for human operator rotations and subjective sense of time

Measuring Workload Differences Between Short-term Memory and Long-term Memory Scenarios in a Simulated Flight Environment

Four highly experienced Air Force pilots each flew four simulated flight scenarios. Two scenarios required a great deal of aircraft maneuvering. The other two scenarios involved less maneuvering, but required remembering a number of items. All scenarios were designed to be equaly challenging. Pilot's Subjective Ratings for Activity-level, Complexity, Difficulty, Stress, and Workload were higher for the manuevering scenarios than the memory scenarios. At a moderate workload level, keeping the pilots active resulted in better aircraft control. When required to monitor and remember items, aircraft control tended to decrease. Pilots tended to weigh information about the spatial positioning and performance of their aircraft more heavily than other items

Expert system training and control based on the fuzzy relation matrix

Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model

The impact of physical and mental tasks on pilot mental workoad

Seven instrument-rated pilots with a wide range of backgrounds and experience levels flew four different scenarios on a fixed-base simulator. The Baseline scenario was the simplest of the four and had few mental and physical tasks. An activity scenario had many physical but few mental tasks. The Planning scenario had few physical and many mental taks. A Combined scenario had high mental and physical task loads. The magnitude of each pilot's altitude and airspeed deviations was measured, subjective workload ratings were recorded, and the degree of pilot compliance with assigned memory/planning tasks was noted. Mental and physical performance was a strong function of the manual activity level, but not influenced by the mental task load. High manual task loads resulted in a large percentage of mental errors even under low mental task loads. Although all the pilots gave similar subjective ratings when the manual task load was high, subjective ratings showed greater individual differences with high mental task loads. Altitude or airspeed deviations and subjective ratings were most correlated when the total task load was very high. Although airspeed deviations, altitude deviations, and subjective workload ratings were similar for both low experience and high experience pilots, at very high total task loads, mental performance was much lower for the low experience pilots

Effect of time span and task load on pilot mental workload

Two sets of experiments were run to examine how the mental workload of a pilot might be measured. The effects of continuous manual control activity versus discrete assigned mental tasks (including the length of time between receiving an assignment and executing it) were examined. The first experiment evaluated the strengths and weaknesses of measuring mental workload with an objective perforamance (altitude deviations) and five subjective ratings (activity level, complexity, difficulty, stress, and workload). The second set of experiments built upon the first set by increasing workload intensities and adding another performance measure: airspeed deviation. The results are discussed for both low and high experience pilots