A vibratory sensor capable of locating parts by measuring their inertial properties is described in this paper. The sensor is designed to be fitted to the wrist of a robot and used to acquire parts from a stack or a tray. The initial coordinates of the parts need only be approximately known (say to ±25 mm and ±45°). The robot is thus said to operate in a “semi-ordered” environment which can be realised inexpensively as accurate pallets, fixtures or other parts presentation equipment are not required. Furthermore, the absence of complete disorder, as would exist with a “bin-picking” approach where parts are allowed to lie at random in a bin, reduces the degree of sophistication demanded of the sensor system. Consequently, the cost of the latter can also be kept low.

The proposed sensor has a circular platform mounted on the shaft of a motor such that the shaft is normal to the platform. The part whose location is to be determined is held on the platform by magnetic or other means. The assembly consisting of the part, platform and motor is constrained to vibrate about an axis parallel to the platform. Two methods for computing the location of the part relative to the platform are described. Both methods require the natural frequencies of vibration of the part-platform-motor assembly for various angular positions of the platform. A simulation study to examine the effect of various design and operational parameters (inertias of the platform and part, stiffness of the spring restraining the movements of the vibrating assembly, location of part on platform, accuracy of frequency measurements) on the accuracy of the location computed is presented. The simulation results clearly demonstrate the feasibility of the sensor.

A semi-automatic method for calibrating a robot-vision interface is presented. It puts a small work-load on the operator, requires a simple calibration jig and a solution of a very simple system of equations. It has been extensively used in an experimental robotic cell set up at Loughborough University of Technology, where various aspects of the manufacturing and the decoration of scale models are being investigated. As an extension of the calibration procedure, the paper also shows practical solutions for the problem of dealing with three dimensional objects using a single camera.

For the navigation of a mobile robot, the determination of its absolute location is one of essential tasks. This paper proposes a stripe type landmark which enables us to develop a fast algorithm to calculate the distance and orientation of a camera relative to the landmark. Exact and closed form solution of the camera location is obtained from the geometric relation between the pattern of landmark and its projected image. Since the presented algorithm requires only one row of the mark image, determination of the location can be processed in real-time. In addition, the mark can be identified using the projective invariant of the original mark pattern without any additional patterns. The effect of the error sources on the location determination is analyzed through a series of simulations and experiments. The applicability of the algorithm to mobile robots is discussed using the experimental results.

The paper presents a geometric method for collision-free manipulator path planning in 3D Euclidean space with polyhedral obstacles. It ensures that none of the links nor the manipulator tip collide with the objects. The method is computationally very cheap and it does not require intensive off-line preprocessing. Hence, it is real-time applicable if the information about obstacles positions and shapes is obtained from a higher control level. The trajectories generated lie within the reachable workspace. The method is implemented on a VAX 11/750 computer and the simulation results are included.

ISRA is a support system for robot programming. It provides a means to automatically (guided by knowledge) convert a user's request, expressed in the natural language, into the appropriate conceptual model of the required task. This model incorporates information required for the understanding, planning and sensory-guided performance of the required robotic task.

To develop this system we applied the Natural Computation method. We considered natural information processing by humans during synthesis and interpretation of robotic programs, and then constructed an approximate conceptual model of the relevant dynamically changing real world.

Such a model has to be suitable (e.g. representable and executable) for efficient computer processing. This paper presents the results of a case study which shows that methods built by formalizing human information processing in the robotic domain may be efficiently and naturally implemented in ISRA. It provides evidence that the structure and behavior of ISRA's competence representation and algorithm are comparable with the psychological behavior of humans, as required by the Natural Computation method.

The case study illustrates the use of ISRA for the first phase of an assembly program synthesis i.e. planning of all valid assembly sequences.

We consider the problem of sensor-based motion planning for a three-dimensional robot arm manipulator operating among unknown obstacles. When every point of the robot body is subject to potential collision. The corresponding planning system must include these four basic components: sensor hardware; real-time signal/sensory data processing hardware/software; a local step planning subsystem that works at the basic sample rate of the arm; and finally, a subsystem for global planning. The arm sensor system developed at Yale University presents a proximity sensitive skin that covers the whole body of the arm and consists of an array of discrete active infrared sensors that detect obstacles by processing reflected light. The sensor data then undergoes low level processing via a step planning procedure, which converts sensor information into local normals at the contact points in the configuration space of the robot. This paper presents preliminary results on the fourth component, a real-time algorithm that realizes the upper, global level of planning. Based on the current collection of local normals, the algorithm generates preferable directions of motion around obstacles, so as to guarantee reaching the target position if it is reachable. Experimental results from testing the developed system are also discussed.

We have designed, built, and tested a new wheel control system for the HERMIES-III robot. HERMIES-III is a large mobile robot with omnidirectional steering that is designed for human scale experiments. During each cycle (at 20 Hz), the wheel control system moves the robot toward a goal and calculates the current position of the robot. The system has seven modes for moving to a goal and the goal may be changed during motion of the robot.

The performance of robotic manipulators is limited by the nature of the control systems which do not satisfactorily integrate the non-linear phenomena associated with the dynamic behavior of the mechanisms. The significant variations in the axial inertias lead to control problems and require an optimization of the mechanical structures in order to improve the stability of the manipulators. This paper proposes mechanical solutions in the domain of dynamic decoupling of robots and demonstrates, using numerical simulations the value of these solutions in terms of control.

This paper deals with the study of the effects of Harmonic Drives characteristics on the dynamic behaviour of industrial robots. These components are firstly analyzed on the basis of the technical literature and, as a result, a mechanical model with concentrated parameters is obtained. Finally, the influence of these parameters on the dynamic behaviour of an actual SCARA robot in our department is investigated by means of experimental tests and by a computer simulation program purposely written.

Recently, three-dimensional motion analysis and shape recovery have attracted growing attention as promising avenues of approach to image understanding, object reconstruction as well as computer vision for robotic Systems. The image generation problem and the model generation problem are presented. More specifically, the inputs to the image generator are an old image, object model, motion specification, and hidden line and hidden surface algorithms. The output is a new image. Since the object model is given, the top-down approach is usually used. On the other hand, for the model generation problem, the input is an image sequence while the output is an object model. Since the object model is not given, and bottom-up approach is usually used.

In this paper, the largest possible object approach is proposed and the advantages of this approach are stated. They are:

1. This approach may be applicable to objects with planar surfaces as well as nonplanar surfaces.

2. This approach may be applicable to the case that there are more than one face change per frame.

3. This approach may be applicable when the camera is moving.

4. This approach may be applicable when the object is measured by several measuring stations.

By using this approach, algorithms for simple object reconstruction given a sequence of pictures are presented together with illustrative examples. The relevance and importance of this work are discussed.

The results of this paper may have useful applications in object reconstruction, pictorial data reduction and computer vision for robotic Systems.