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

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

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

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

Experimental evaluation of the concept of supevisory manipulation

A computer-controlled teleoperator system which is based on task-referenced sensor-aided control has been developed to study supervisory manipulation. This system, called SUPERMAN, is capable of performing complicated tasks in real-time by utilizing the operator for high-level functions related to the unpredictable portions of a task, while the subordinate machine performs the more well-defined subtasks under human supervison. To determine whether supervisory control schemes such as these offer any advantage over manual control under real-time conditions, a number of experiments involving both simple and complicated tasks were performed. Six representative tasks were chosen for the study: (1) obtaining a tool from a rack, (2) returning the tool to the rack, (3) removing a nut, (4) placing samples in a storage bin, (5) opening and closing a valve, and (6) digging with a shovel. The experiments were performed under simulated conditions using four forms of manual control (i.e., switch rate, joystick rate, master-slave position control, and master-slave with force feedback), as well as supervisory control. Through these experiments the effectiveness and quality of control were evaluated on the basis of the time required to complete each portion of the task and the type and number of errors which occurred

Measurement and display of control information. Remote manipulation and manual control Progress report, 1 Apr. - 30 Sep. 1967

Control interface between man and computer manipulators, and optimality of human controllers as time optimal, bang-bang state regulators of second order system

Modeling human decision making behavior in supervisory control

An optimal decision control model was developed, which is based primarily on a dynamic programming algorithm which looks at all the available task possibilities, charts an optimal trajectory, and commits itself to do the first step (i.e., follow the optimal trajectory during the next time period), and then iterates the calculation. A Bayesian estimator was included which estimates the tasks which might occur in the immediate future and provides this information to the dynamic programming routine. Preliminary trials comparing the human subject's performance to that of the optimal model show a great similarity, but indicate that the human skips certain movements which require quick change in strategy

Effect of time span and task load on pilot mental workload

Two sets of simulations designed to examine how a pilot's mental workload is affected by continuous manual-control activity versus discrete mental tasks that included the length of time between receiving an assignment and executing it are described. The first experiment evaluated two types of measures: objective performance indicators and subjective ratings. Subjective ratings for the two missions were different, but the objective performance measures were similar. In the second experiments, workload levels were increased and a second performance measure was taken. Mental workload had no influence on either performance-based workload measure. Subjective ratings discriminated among the scenarios and correlated with performance measures for high-workload flights. The number of mental tasks performed did not influence error rates, although high manual workloads did increase errors