Methods and strategies of object localization

An important property of an intelligent robot is to be able to determine the location of an object in 3-D space. A general object localization system structure is proposed, some important issues on localization discussed, and an overview given for current available object localization algorithms and systems. The algorithms reviewed are characterized by their feature extracting and matching strategies; the range finding methods; the types of locatable objects; and the mathematical formulating methods

Tele-Autonomous control involving contact

Object localization and its application in tele-autonomous systems are studied. Two object localization algorithms are presented together with the methods of extracting several important types of object features. The first algorithm is based on line-segment to line-segment matching. Line range sensors are used to extract line-segment features from an object. The extracted features are matched to corresponding model features to compute the location of the object. The inputs of the second algorithm are not limited only to the line features. Featured points (point to point matching) and featured unit direction vectors (vector to vector matching) can also be used as the inputs of the algorithm, and there is no upper limit on the number of the features inputed. The algorithm will allow the use of redundant features to find a better solution. The algorithm uses dual number quaternions to represent the position and orientation of an object and uses the least squares optimization method to find an optimal solution for the object's location. The advantage of using this representation is that the method solves for the location estimation by minimizing a single cost function associated with the sum of the orientation and position errors and thus has a better performance on the estimation, both in accuracy and speed, than that of other similar algorithms. The difficulties when the operator is controlling a remote robot to perform manipulation tasks are also discussed. The main problems facing the operator are time delays on the signal transmission and the uncertainties of the remote environment. How object localization techniques can be used together with other techniques such as predictor display and time desynchronization to help to overcome these difficulties are then discussed

Integrated inpection of sculptured surface products using machine vision and a coordinate measuring machine

In modem manufacturing technology with increasing automation of manufacturing processes and operations, the need for automated measurement has become much more apparent. Computer measuring machines are one of the essential instruments for quality control and measurement of complex products, performing measurements that were previously laborious and time consuming. Inspection of sculptured surfaces can be time consuming since, for exact specification, an almost infinite number of points would be required. Automated measurement with a significant reduction of inspected points can be attempted if prior knowledge of the part shape is available. The use of a vision system can help to identify product shape and features but, unfortunately, the accuracy required is often insufficient. In this work a vision system used with a Coordinate Measuring Machine (CMM), incorporating probing, has enabled fast and accurate measurements to be obtained. The part features have been enhanced by surface marking and a simple 2-D vision system has been utilised to identify part features. In order to accurately identify all parts of the product using the 2-D vision system, a multiple image superposition method has been developed which enables 100 per cent identification of surface features. A method has been developed to generate approximate 3-D surface position from prior knowledge of the product shape. A probing strategy has been developed which selects correct probe angle for optimum accuracy and access, together with methods and software for automated CMM code generation. This has enabled accurate measurement of product features with considerable reductions in inspection time. Several strategies for the determination and assessment of feature position errors have been investigated and a method using a 3-D least squares assessment has been found to be satisfactory. A graphical representation of the product model and errors has been developed using a 3-D solid modelling CAD system. The work has used golf balls and tooling as the product example

\u3cem\u3eGRASP News\u3c/em\u3e, Volume 6, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory, edited by Gregory Long and Alok Gupta

Automatic recognition of three dimensional planar objects by Hough transform type operations

This thesis describes an investigation into the recognition from range data of three dimensional objects with plane surfaces. In it a Hough transform type operation is used to identify objects. This is adapted for three dimensions and uses a voting scheme to identify objects. First, all available edges of the object present in the scene are extracted. Then, two edges of the object and two lines of a model are taken at a time. These are pruned and potential matching lines are selected. Next, geometric transformations necessary to take them into a fixed position in space are calculated. Matrices resulting from successful matches are computed and stored. The presence of an object similar to a model results in the generation of the same matrices. Recognition is achieved by choosing the model with the highest occurring matrix. In order to extract edges a vision system is designed and set up. In it a stripe of light generated from the projector together with a camera is employed. A procedure to calibrate the system and extract three dimensional information is devised. Then objects are scanned and from the images taken, coordinates of edge points are computed. Next, edge points are linked and edges of the object are extracted and a recognition algorithm is applied. The system is tested on objects with varying complexity. Recognition is performed in two different categories. First objects are placed on a specific face. Then they are recognised in arbitrary position and orientation. For each object the results and implications of the recognition algorithm, are investigated. A modified version of the recognition algorithm with two and three connected lines is tested and compared with previous experiments

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement

Egomotion estimation using binocular spatiotemporal oriented energy

Camera egomotion estimation is concerned with the recovery of a camera's motion (e.g., instantaneous translation and rotation) as it moves through its environment. It has been demonstrated to be of both theoretical and practical interest. This thesis documents a novel algorithm for egomotion estimation based on binocularly matched spatiotemporal oriented energy distributions. Basing the estimation on oriented energy measurements makes it possible to recover egomotion without the need to establish temporal correspondences or convert disparity into 3D world coordinates. There sulting algorithm has been realized in software and evaluated quantitatively on a novel laboratory dataset with ground truth as well as qualitatively on both indoor and outdoor real-world datasets. Performance is evaluated relative to comparable alternative algorithms and shown to exhibit best overall performance

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

Proceedings of the NASA Conference on Space Telerobotics, volume 3

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research