This paper describes an autonomous robot vehicle which can navigate through an initially unknown obstacle field to a nominated goal or systematically map its working environment. The navigation system uses combined ultrasonic beacon/odometry based localisation, optical range finders for environmental mapping, an A path planning procedure and continuous motion control. The computational support is divided between a graphics workstation 'home base' and a PC hosted transputer array on-board. The integration of all the subsystems cited above has been achieved and many successful navigation experiments completed. Possible further developments which would enhance the capabilities of the system are also discussed.

A general method is presented to automatically determine the placement of manipulators which allows one to optimize multiple kinematic performances indices during the execution of their tasks. It considers the presence of obstacles in the workstation and constraints on the motion of the manipulator's joints. The complete formulation is included, and an example with a six-degree-of-freedom manipulator in a cluttered environment es solved that demonstrates the improvements achieved for the manipulator performances by applying the method.

Almost all industrial robot applications in use today are controlled using a control law that is simple and computationally efficient, local joint error feedback. When two or more open chain manipulators cooperate to manipulate the same object - such as in mechanical grippers, walking machines, and cooperating manipulator systems - closed kinematic chain, redundantly actuated mechanisms are formed. Control approaches for this type of system focus on the more computationally intensive computed torque or inverse plant control laws, due to the concern over instability caused by the unspecified distribution of control forces in the redundant actuator space, and due to the constrained motion caused by the closed kinematic chains.

A modular hierarchical model for controlling robots is presented. This model is targeted mainly for research and development; it enables researchers to concentrate on a certain specific task of robotics, while using existing building blocks for the rest of their applications. The presentation begins by discussing the problems with which researchers and engineers of robotics are faced whenever trying to use existing commercial robots. Based on this discussion we propose a new general model for robot control to be referred as TERM (TEchnion Robotic Model). The viability of the new model is demonstrated by implementing a general purpose robot controller.

This paper presents a Kalman filtering technique for reducing errors in locating 3-D objects using a sensor system. The location information is employed to control the motion of an industrial robot to pick up the objects. The sensor consists of a rigid platform mounted on a flexible column. Each object to be located is placed on the sensor. The static deflections and natural frequencies of vibrations of the sensor are measured and processed to determine the position and orientation of the object. In practice, the sensor signals obtained are corrupted with noise leading to errors in location determination. A Kalman filter is used to reduce the noise present in the sensor system.

This paper presents a new approach for simplifying dynamic equations of motion of robot manipulators by using a nondimensionalization scheme. With this approach the dynamic analysis is done in a nondimensional space. That is, it is required to establish a dimensionless coordinate system in which the dynamic equations of motion of manipulators are formulated. The characteristic parameters of the manipulators are then defined by choosing proper physical quantities as basic units for nondimensionalization. Within the nondimensional space the Lagrange method is applied to the manipulator to obtain a set of general dimensionless equations of motion. This dimensionless dynamic formulation of manipulators leads to an easier way to simplify the dynamic formulation by neglecting insignificant terms using the order of magnitude comparison. The dimensionless dynamic model and its simplified version of PUMA 560 robot are implemented using the proposed approach. It is found that the simplified dynamic model greatly reduces the computation burden of the inverse dynamics. Simulation results also show that the simplified model is extremely accurate. This implies that the proposed nondimensional simplification emethod is reliable.

The application of the joint force sensory feedback in both the gross and fine motion control of manipulation robots is considered in the paper. One of the objectives of the paper is to give a historical overview how the idea of the joint force sensory feedback has appeared and developed in the past two decades. The control schemes, which include joint torque sensory feedback, are surveyed in the paper. The main advantages of this approach are discussed: the joint torque feedback offers an elegant way to compensate for the effects of the robot dynamics without real time computation of the robot dynamics, the control schemes are robust in respect of parameter variations. Various problems regarding design and implementation of joint torque sensor are also considered. Special emphasis is given to the application of this approach in hybrid position/force control schemes.

For a kinematically redundant manipulator, some performance indices can be optimized while carrying out a given task. So far, the redundancy resolution has been solved at the joint angle level, the joint velocity level, or joint acceleration level depending on the performance indices. According to the resolution level, the solution is represented by high-order differential equations or superfluous number of equations. We propose a unified approach to the inverse kinematic solution which optimizes it at the joint velocity level regardless of the types of the performance indices. A unified approach to obtain an optimal joint velocity is derived by using the necessary condition for optimality so that the proposed method provides an optimal solution for any performance indices and tasks. The optimal solution becomes a set of the minimum number of first-order differential equations which requires a minimum search dimension.To show the validity of the approach, it is applied to a three-link planar manipulator for various types of performance indices.

This paper deals with the synthesis of a robot mechanism, which has an open kinematic chain structure. The aim of the synthesis is to find optimal mechanism link lengths and the elevation of the robot mechanism base, with respect to the arbitrary chosen task which is described in a task space.

A mathematical model, which describes the problem and enables one to use a nonlinear optimization algorithm, was developed. The usefulness of the approach is demonstrated by the example of the Manutec r3 mechanism with a prescribed task for the robot's end-effector.

This paper describes a new approach to the automatic generation of assembly precedence constraints for robotic assembly, using a part contact level graph. Since inference of precedence constraints is a prerequisite to generate assembly sequences of a product, much work has been done in this field. However, most of it has some limitations in that they use a cumbersome user query or time-consuming geometric reasoning. To cope with these problems, this paper utilizes three directional part contact level graphs which, in three orthogonal directions, contain the information on directional connections for each pair of mating parts. By using these graphs, an assembly precedence constraint is inferred in two steps: The first step infers a precedence constraint for each directional connection by applying the path-finding algorithm. Utilizing the precedence constraints thus obtained, the next step infers the precedence constraint for each part to be assembled with its base assembly. Examples are given to illustrate the concepts and procedure of the proposed scheme.

This paper, as an extension of an earlier paper, presents a geometrical representation and theoretical foundation of robot grasping that is affected by friction and by the magnitudes of normal contact forces. Grasp analysis and synthesis are based on the concepts of constraint cone (region), restraint cone and freedom cone in the force screw-space and location screw-space. In fact, the freedom cone is the aggregate of all the screws repelling and reciprocal to the grasp geometry (denoted by the restraint cone). Moreover, the constraint cone and the constraint region describe the effect of friction and the influence of the amplitudes of normal forces. The conditions of equilibrium grasp, stable grasp, form closure, force closure, and relative form closure are derived from the geometrical representation, and approaches are suggested for the design of adaptable fixtures, and for automatic grasp planning. It is shown that relative form closure is of great significance for frictional grasp, since it is possible to generate enough internal forces in the subspace spanned by the contacts and consequently produce corresponding friction forces in the reciprocal subspace.

The names of the authors of ‘Explicit Path Tracking by Autonomous Vehicles’ Robotica 10, Part 6, 539–554 (1992) should be Dong Hun Shin and Sarjiv Singh, and not as indicated. (Editor).