The long-term objectives of this four-year project address three specific aims related to human performance during space telerobotics training. We are collaborating with the Johnson Space Center Robotic Systems Training Group. The project is in its second year.

Specific Aims

1. Our goal is to improve NASA teleoperation training efficiency by scientifically customizing remedial training based on the measured spatial abilities of individual astronauts. Astronaut robotics trainees vary significantly in their initial performance, ability, learning rate and level of mastery. Because the process of training astronauts to be qualified robotics operators is so long and expensive, NASA needs tools to predict robotics performance prior to training. NASAs existing Aptitude for Robotics Test (ART) had not been statistically validated. Using a logistic modeling approach, we investigated how well an astronauts ART scores predicted his/her spatial performance in subsequent evaluation testing with either Shuttle Payload Deployment and Retrieval System or Generic Robotics Training. ART was not found to be a reliable predictor. Based on our data analysis, we proposed changes in ART performance metrics to improve the predictive power. These have now been implemented and are being used in the current round of astronaut candidate testing. We expect to re-evaluate the modified ART dataset in Year 4.

   Also, we tested the mental rotation and perspective taking spatial abilities of 40 active astronauts who had completed at least one robotics training course. We found logistic regression models that predicted who would achieve the top score in qualification evaluations. The model predictions appear reliable enough to be used to customize regular and remedial training but not to make career defining decisions. The models could not reliably predict who would completely fail because so few did. We have proposed improvements in GRT scoring methodology that should improve prediction reliability. At Johnson Space Centers request, we are also evaluating whether GRT scores could be used to predict performance in later training (e.g. Space Station Remote Manipulator), or under operational conditions on the International Space Station (ISS).

2. Our second major objective is to perform experiments using a space telerobotics training simulator at Massachusetts Institute of Technology (MIT) to quantify how a trainees individual spatial and manual control abilities, use of camera views and hand-controller reference frame impacts learning and final level of performance as both a primary and secondary robotics operator. This aim was the main focus of our activity this year. We hypothesized that individual ability to manipulate the arm and integrate camera views correlates with three subcomponents of spatial intelligence: spatial visualization (SV), mental rotation (MR) and perspective taking (PT). In particular, PT (the ability to imagine an object from another viewpoint) was thought to be important for integrating camera views. This year we completed three different experiments using MITs Dynamic Skills Trainer, a virtual space telerobotic training system similar to that used at JSC:

   In the first experiment, 19 subjects were trained to manipulate a robotic arm using a pair of hand controllers in a virtual environment almost identical to that in NASAs Basic Operational Robotic Instruction System (BORIS), used in NASAs introductory Generic Robotics Training course. Over 18 fly to trials, the disparity between the arm's control frame and the cameras were varied between low (< 90 degrees) and high (> 90 degrees) conditions. We used the Cube Comparisons test to assess SV, the Vandenberg Mental Rotations Test (MRT) to assess MR, and the Purdue Spatial Visualization of Views Test (PSVT) and a Perspective Taking Ability (PTA) test to assess PT. We showed that subjects with high PSVT scores moved the arm more directly to the target and were better at maintaining the required clearance between the arm and obstacles, even without a direct camera view. The subjects' performance degraded under the high disparity condition.

   Our second experiment addressed trainee performance as both primary and then secondary (monitoring) operator. Twenty subjects were trained to manipulate the arm during six trials in a BORIS environment and then acted as a secondary operator observing an additional 32 trials in an ISS-like environment. We recorded which of three display monitors the trainee was looking at. The MRT, PSVT, and PTA were used to assess spatial abilities. Though the primary operator task was slightly different than that used in Experiment 1, we prospectively confirmed many results of the first experiment. Subjects with high PTA scores took less time, moved the arm more directly to the target, and moved the arm more fluidly, especially under the high disparity condition. High scorers on the PSVT and PTA were better at maintaining required clearance. Low PTA scorers looked from monitor to map more often. Prior experience with the arm did not significantly improve task performance, and performance as primary operator did not reliably predict performance as a secondary operator. However, subjects with high PSVT scores had better overall secondary operator performance and high PTA scorers were better at detecting problems before they occurred.

3. Our third major goal is to identify and develop new interfaces and tools to support future in-space, lunar surface teleoperation and teleoperation training. Our original 2007 plan was to develop an adjunct spatial situation display and a scheme for switching camera views using operator gestures. We plan to focus on bimanual control skill assessment this year while acquiring the necessary tracking hardware and will address gesture control or spatial situation displays during Year 4.

Project Description
NASA Task Book Entry