Tarek Khaled Alameldin

An adaptive and efficient system for computing the 3D reachable workspace

An efficient system for computing the 3D reachable workspace for redundant manipulators with joint limits is presented. In this system, the 3D reachable workspace problem is decomposed into two major subproblems. They are workspace point generation and surface computation. Different algorithms are described that are used to build these modules. The advantages offered by the system include modularity, flexibility, parallel implementation, adaptability, and generality

Complexity of computing reachable workspaces for redundant manipulators

The complexity ofcomputing 3D workspaces forjoint limited redundant manipulators is examined. Different types of reachable workspace volume and reachable workspace boundary problems are defined. Each type of volume problem is at least as hard as its corresponding type of boundary problem and each problem type is at least NP hard. New efficient and adaptive workspace point computation techniques are proposed (e. g. based on nonlinear programming) after complexity analyses of the corresponding decision problems.

On the evaluation of reachable workspace for redundant manipulators

In this paper, we discuss the problem of computing the reachable workspace for redundant manipulators. Algorithms that compute workspace boundary points by using screw theory are presented. These algorithms cannot distinguish holes and voids that are buried within the reachable workspace. We present an algorithm that utilizes inverse kinematics in order to detect the unreachable regions (holes and voids) within the reachable workspace.

Parallel algorithm for computing 3-D reachable workspaces

The problem of computing the 3-D workspace for redundant articulated chains has applications in a variety of fields such as robotics, computer aided design, and computer graphics. The computational complexity of the workspace problem is at least NP-hard. The recent advent of parallel computers has made practical solutions for the workspace problem possible. Parallel algorithms for computing the 3-D workspace for redundant articulated chains with joint limits are presented. The first phase of these algorithms computes workspace points in parallel. The second phase uses workspace points that are computed in the first phase and fits a 3-D surface around the volume that encompasses the workspace points. The second phase also maps the 3- D points into slices, uses region filling to detect the holes and voids in the workspace, extracts the workspace boundary points by testing the neighboring cells, and tiles the consecutive contours with triangles. The proposed algorithms are efficient for computing the 3-D reachable workspace for articulated linkages, not only those with redundant degrees of freedom but also those with joint limits.

Three-dimensional perception and recognition under uncertainty

This paper presents an efficient system for recovering the structural properties of objects with unknown 3-D shape. In this approach, we build adaptive maps for interpreting the object structure under uncertainty. We decompose the system into four major modules: sensing interface, knowledge base, map building and decision making, and the controller. The sensing interface acquires visual data and performs low and intermediate vision tasks for enhancing the acquired image sequences. The knowledge base contains different visual primitives and the possible exploratory actions. The map building and decision making module utilizes the different predicates that are stored in the knowledge base in order to resolve possible uncertainties. The decisions made in the map building and decision making module are then utilized by the controller module which resolves possible uncertainties. The decisions made in the map building and decision making modules are then utilized by the controller module which resolves possible inconsistencies. The above process is repeated until the map stored in the third module contains a minimal number of three dimensional interpretations that cannot be reduced further. Motion primitives are used as sensing actions. Uncertainty models are developed for the sensor and for the image processing techniques being used. Further filtering and a rejection mechanism are then developed to discard unrealistic motion and structure estimates. This system is capable of recognizing the object structure efficiently and adaptively.

Efficient system for 3-D object recognition

This paper presents an efficient system for recovering the structural properties of objects. We build adaptive maps for interpreting the object structure. The System is decomposed into four major modules, the sensing interface acquires visual data and performs low and intermediate vision tasks for enhancing the acquired image sequences. A knowledge base contains different visual primitives and the possible exploratory actions. The map building and decision making module gets its input from the sensing interface and utilizes the different predicates that are stored in the knowledge base in order to resolve possible uncertainties. The decisions made in the map building and decision making module are then utilized by the controller module which resolves possible inconsistencies due to physical limitations of the sensing devices. The above process is repeated until the map contains a minimal number of interpretations that cannot be reduced further.

Structure and motion of entire polyhedra

We describe an efficient system for recovering the 3-D motion and structure of entire polyhedra from an evolving image sequence. The suggested technique utilizes the image flow velocities in order to recover the 3-D parameters. We develop a method for estimating the image flow velocities and an algorithm for computing the 3-D parameters given two successive image frames. The solution is then improved by using a large number of image frames and exploiting the temporal coherence of 3-D motion. We use the ordinary differential which describe the parametric evolution in terms of the current motion/structure and the measurements in the image plane. The extended Kalman filter is then used to update the solution. The process is started by segmenting the entire scene into a number of planar surfaces and then applying the above technique to each surface under consideration the probable inconsistencies are then resolved.

Operator/system communication: an optimizing decision tool

Abstract In this paper we address the problem of operator/system communication. In particular, we discuss the issue of efficient and adaptive transmission mechanisms over possible physical links.We develop a tool for making decisions regarding the flow of control sequences and data from andto the operator. The issue of compression is discussed in details, a decision box and an optimizingtool for finding the appropriate thresholds for a decision are developed. Physical parameters likethe data rate, bandwidth of the communication medium, distance between the operator and the system, baud rate, levels of discretization, signal to noise ratio and propagation speed of the signal are taken into consideration while developing our decision system. Theoretical analysis isperformed to develop mathematical models for the optimization algorithm. Simulation modelsare also developed for testing both the optimization and the decision tool box. 1 Introduction Data which is transmitted over a communication medium between the operator and the system, whichmight be a mobile robot, contains some form of redundancy. This redundancy can be exploited tomake economical use of the storage media or to reduce the cost of transferring the data and commandsover the communication network. One of the basic issues in the design of the presentation layer is todecide whether data is to be compressed before transmission or not. Many factors may affect making

A system for recovering 3-D motion and structure

We discuss the problem of recovering the 3-D motion and structure. An algorithm for computing the camera motion and the orientation of planar surface is developed. It solves for the 3-D motion and structure iteratively given two successive image frames. We improve the solution by solving the ordinary differential equations which describe the evolution of motion and structure over time. The solution is further improved by exploiting the temporal coherence of 3-D motion. We develop the ordinary differential equations which describe the evolution of the parameters in terms of the current parameters and the measurements. The extended Kalman filter is then used to update the solution of the differential equations. The robustness of the entire process is demonstrated by the experiment with a moving camera which “flies” over a terrain model.