New developments of edge matching based semiautomatic virtual reality calibration are presented to provide more reliable and accurate telerobotic servicing. Three basic algorithms employed are (1) weighted average local edge detector, (2) weighted least squares for the edge-based camera calibration and object localization, and (3) robust matching to remove outliers. A key new 20-variable least-squares algorithm is developed that updates both the camera and the object models simultaneously for given two camera views of two mating objects. This simultaneous update reduces relative positioning errors considerably, and is essential to achieve high alignment precision. The developed system has been successfully tested for an ORU (Orbital Replacement Unit) insertion task within a /spl plusmn/1/4 inch and /spl plusmn/3/spl deg/ alignment precision.

A program to develop planetary rover technology is underway at the Jet Propulsion Laboratory (JPL) under sponsorship of NASA. Developmental systems with the necessary sensing, computing, power, and mobility resources to demonstrate realistic forms of control for various missions have been developed, and initial testing has been completed. These testbed systems and the associated navigation techniques used are described. Particular emphasis is placed on three technologies: Computer-Aided Remote Driving (CARD), Semiautonomous Navigation (SAN), and behavior control. It is concluded that, through the development and evaluation of such technologies, research at JPL has expanded the set of viable planetary rover mission possibilities beyond the limits of remotely teleoperated systems such as Lunakhod. These are potentially applicable to exploration of all the solid planetary surfaces in the solar system, including Mars, Venus, and the moons of the gas giant planets.>

A method of matching unequally spaced height maps is described. This method would be useful in a Mars rover which tries to refine the estimate of its position by matching the data from its stereo vision system or laser rangefinder to data obtained from a camera orbiting Mars. The refined position can be used to merge the two sets of data with proper registration. The method is designed to make full use of the information contained in the data, including accuracy estimates in the form of covariance matrices and reliability estimates in the form of probabilities. Means of extracting this information from stereo vision are discussed. The terrain matching process uses a coarse-to-fine strategy, and it includes automatic editing to remove points with excessive disagreement. An example using real data from an experimental vehicle is presented.>

A useful space telerobot for on-orbit assembly, maintenance, and repair tasks must have a sensing and perception subsystem which can provide the locations, orientations, and velocities of all relevant objects in the work environment. This function must be accomplished with sufficient speed and accuracy to permit effective grappling and manipulation. Appropriate symbolic names must be attached to each object for use by higher-level planning algorithms. Sensor data and inferences must be presented to the remote human operator in a way that is both comprehensible in ensuring safe autonomous operation and useful for direct teleoperation. Research at JPL toward these objectives is described.