A parallel-processing system for locating parts and controlling an industrial robot is proposed. The system employs Transputers and Occam to achieve parallelism. In conjunction with a novel vibratory sensor, the system enables a robot to determine the exact location of parts which have been picked up from a semi-ordered work place. A new algorithm for obtaining the coordinates of the parts using the sensed vibration and deflection signals is described. The algorithm dispenses with the lengthy and complex equation-solving procedures previously required. Instead, it only involves looking up a data table and performing simple two-dimensional interpolation calculations. The design of the algorithm to ensure efficient parallel operation is described. Experimental results showing the successful implementation of the algorithm on the proposed system are presented.

The DELTA parallel robot, designed by an EPFL (Ecole Polytechnique Fédérale de Lausanne) research team, is a mechanical structure which has the advantage of parallel robots and ease of serial robots modeling. This paper presents solutions for a complete modeling of the DELTA parallel robot (direct and inverse kinematics, inverse statics, inverse dynamics), with few arithmetic and trigonometric operations. Our method is based on a satisfactory choice of kinematic parameters and on a few restricting hypotheses for the static and dynamic models. We give some details of each model, we present some computation results and we put the emphasis on some particular points, showing the capabilities of this mechanical structure.

Robots will require some form of proximity sensing in order to perform many delicate exploration, assembly and manipulation tasks. This paper describes a novel articulated tactile probe which can locate and accurately measure the 3-dimensional surface contours of small objects. Although lacking the speed of data acquisition possible with vision and other non-contact sensors, the resulting data is easily processed to give useful information about an object.

The payload capacity of a conventional robot is usually limited as compared to the mass of the robot body. This is because a payload adds additional gravity loadings to the robot joints resulting in large input joint torques. To reduce the required input joint torques, the authors have proposed a mechanical balancing mechanism. Basically, the mechanism was designed to exactly balance the first three links of an articulated robot by adjusting the positions of counter-balancing masses so as to eliminate the gravity loading terms. Since the input joint torques are greatly reduced by adopting balancing mechanisms, a balanced robot is expected to carry heavier payload and move with higher speed and acceleration. This paper further investigates the possibilities of improving the payload capacity as well as speed and acceleration capabilities. These features were investigated under various operating conditions involving payload, maximum angular velocity, and acceleration period. Based upon the simulation results, the performances of the balanced robot are compared in detail with those of a unbalanced conventional robot.

The paper considers the highest control level organization of a flexible manufacturing cell (FMS). The indeterminancy problem in Petri nets is discussed as well as a method for overcoming it by two control levels. The net is decomposed into individual robot nets and machines. A simple language for defining robot activation conditions is developed and used for defining knowledge base contents. A method for linking it with other control modules is given. Also, the solution performance is analysed.

This paper is concerned with the dynamic merit of robot manipulators and method for the optimization of manipulator dynamics in the case of an extremely bad design, which can be put into three categories: 1. Acceleration performance: minimize 2. Velocity performance: minimize 3. Comprehensive performance: minimize , and are the dynamics indices of API, VPI and CD PI under various conditions respectively.

The exchange algorithm is presented and a procedure is developed to solve this kind of Minimax problem. An example is discussed to illustrate the application of the optimization method. The large uniform magnitude of a joint relative driving torque provided by this dynamics optimization procedure will be made into a large work space and large torques.

This paper presents a collision-free motion planning method of two articulated robot arms in a three dimensional common work space. Each link of a robot arm is modeled by a cylinder ended by two hemispheres, and the remaining wrist and hand is modeled by a sphere. To describe the danger of collision between two modeled objects, minimum distance functions, which are defined by the Euclidean norm, are used. These minimum distance functions are used to describe the constraints that guarantee no collision between two robot arms. The collision-free motion planning problem is formulated as a pointwise constrained nonlinear minimization problem, and solved by a conjugate gradient method with barrier functions. To improve the minimization process, a simple grid technique is incorporated. Finally, a simulation study is presented to show the significance of the proposed method.

Inertial Measurement Systems (IMS) allow the position calculation of moving objects without requiring outside information. For years the inertial 3-D coordinate measuring technique has been subject to intense research in geodesy and autonomous navigation of land-, water-and airborne vehicles. Because of these areas of application inertially-based systems have been designed for long term measuring only. Here we discuss the requirements that are imposed on inertial sensors in order for them to be used for the calculation of positions of robots. The use of modern sensor technology, combined with strategies for error correction, can result in substantial advantages when calculating robot positions independently from load and environment.

Building Management Systems and Home Automation are, at present, active areas of research and development. One of the unsolved problems within this field is that of Occupant Location within a premises. Computer vision systems are, as yet, too expensive and still not entirely adequate to monitor occupation from every room in a building. The use of existing movement sensors is a cost effective solution but has the disadvantages of not detecting people who are stationary for some time, or giving any indication of how many people are in a room.

This paper addresses the problem of using the collaborative sum of these simple movement sensors in a temporal reasoning scheme to deduce room occupation.

Recent development of sensor knowledge representation by the use of a certainty grid has been extensive and shown the usefulness of the grid-based concept for robot navigation.

Yet the methodology was not perfect. This paper introduces the Bayesian formula into the certainty grid representation to overcome some difficulties of ad hoc formula that has been the only way of updating the grids. The complete derivation of the proposed updating formula is given and proved to be able to accurately identify the simulated world. Also, the paper suggests two updating models: context-sensitive and context-free. Both of them were shown to be usable through simulation in real world modeling.