This paper proposes a method for finding an optimal geometric robot trajectory to perform a specified point-to-point motion without violating joint displacement limits or interference constraints. The problem is discretised, and a quantitative measure of interference is proposed. Constraint violations are represented by exterior penalty functions, and the problem is solved by iteratively improving an initial estimate of the trajectory. This is accomplished by numerically minimizing a cost functional using a modified Newton–Raphson method.

Artificial Intelligence clearly influences Robotics, but the advent of the latter alters the character of A.I. itself, bringing it closer to natural intelligence. This is partly due to greater attention to processes depending on continuous variables, and the combination of these with concept-based or “logical” processes. Some fundamental A.I. principles, notably Minsky's heuristic connection, involve continuity, and the advent ofRobotics should stimulate developments which take them into account. A scheme for a robot which can increase its speed of operation by a learning process is outlined.

This paper presents an advanced control system for an active compliant device. This device, a manipulator-gripper, was designed to achieve stable grasp of objects with various shapes and to impart compliant fine motions to the grasped object. In the control system of this end-effector, we introduced autonomous reasoning capabilities. Fine motion strategies, needed for mating or grasping, use inductive learning from experiments to achieve uncertainty and error recovery. An overview of the articulated gripper's structure is provided for a better understanding of the programming environment we propose. For solving the problem of synthesis programs for fine motion planning we introduce declarative programming facilities in the controller through a time-sensitive mini-prolog. The paper gives some details on the implementation of this mini-prolog. We develop a heuristic procedure to obtain an implicit local model of contacts in complex assembly tasks. Finally, a specific example of this approach – a peg-in-hole operation– –is outlined.

This paper reports on a continuation of research activities at the Loughborough University of Technology (LUT) which are aimed at evolving second generation pneumatic drives and provides an introduction to various aspects which must be considered in the design and use of industrial pneumatic servo-driven robots. The paper illustrates how a new generation of fast and accurate pneumatic servo drives, demonstrating excellent performance/cost characteristics, will become available and will rival electric and hydraulic counterparts in many areas of industrial control.

A nonlinear feedback control based on inverse dynamics is proposed for robots with flexible joints during constrained motion task execution. Based on constrained system formalism, the presented control scheme achieves simultaneous, independent control of both position and contact force at the robot end-effector. The method can be directly applied to robot control, or it can be used as the basis for developing other advanced control strategies. In this paper, a. feedforward controller is considered. Issues related to the practical application of the full inverse dynamics and feedforward control algorithms, such as evaluation of feedback variables, the use of predictors to eliminate the time delay of digital control, and the design of robust controllers, are discussed. The results of extensive numerical simulation are used to show the effectiveness of the proposed controllers and to compare their performances. It is shown that it is possible to achieve high precision tracking if the appropriate predictors are used to eliminate the effect of computational delay of the digital controller. Applying a straightforward approach for robustness of the proposed controllers has additionally improved the trajectory tracking accuracy.

An algorithm for the motion planning of the multifingered hand is proposed to generate finite displacements and changes in orientation of objects by considering sliding contacts as well as rolling contacts between the fingertip and the object at the contact point. Specifically, a nonlinear optimization problem is firstly formulated and solved to find the minimum joint velocity and the minimum contact force to impart a desired motion to the object at each time step. Then, the relative velocity at the contact point is found by calculating the velocity of the fingertip and the object at the contact point. Finally, time derivatives of the surface variables and the contact angle of the fingertip and the object at the current time step is computed using the Montana's contact equation to find the contact parameters of the fingertip and the object at the next time step. To show the validity of the proposed algorithm, a numerical example is illustrated by employing the robotic hand manipulating a sphere with three fingers each of which has four joints

The aim of the research work described in this paper was to study the versatility and effectiveness of commercially available all-purpose robot grippers. In particular, the authors analyzed the capabilities of a two-finger, parallel-action gripper. Another aspect considered in this investigation was the relationship between motion economy and a variety of factors, viz. programming method, gripping configuration, speed of the robot's movement and the weight of the workpiece being handled, all from a standpoint of gripping effectiveness. The potential value of this research work is threefold, involving a knowledge of robot systems limitations, alternate gripping approaches and the development of an extendable gripping analysis method. Further research work is anticipated for a variety of different grippers and robotic arms.