In the field of robotic applications based on the coordinated motion of two manipulators, it seems that very few control schemes work efficiently. The best way to achieve the simultaneous control of object trajectory and forces applied to it, is to implement control schemes that are extended versions of one arm hybrid force'position control. The aim of this paper is not to review all existing solutions but rather to analyze and compare them from simulation results with a new solution presented here. The control scheme is an application of the one arm hybrid external control that we had previously developed. The main results of this theory are summarized in this paper. This radically new approach for a cooperation task has some advantages compared to other methods mentioned in this paper.

This paper is focused on task scheduling in multiprocessor robot controllers. To minimize the input-output time delay our consideration is restricted to parallel architectures that include complete crossbar interconnection networks. In this paper, an efficient scheduling algorithm based on a heuristic function is considered. This function takes into account delays caused by interprocessor communication and minimizes both the execution time and the communication cost. Robot control computation based on a highly efficient customized symbolic method is decomposed into a large number of simple tasks, each involving a single floating-point operation. Starting with an empty partial schedule, each step of the search extends the current partial schedule by adding one of the tasks yet to be scheduled. The heuristic function used in the algorithm actively directs the search for a feasible schedule, i.e. it helps choose the task that extends the current partial schedule. To increase the computational rate we introduced overlapping of computations.

A potential panel method is proposed to solve simultaneously the path planning and collision avoidance problem for a mobile robot operating in an uncertain obstacle filled environment. The problem is solved in three steps: (1) transform the arbitrary shaped obstacles in the 2-D workspace into simple convex polygons; (2) generate a local minima-free potential field on the workspace; (3) generate a streamline from the starting position towards the goal position in the artificial potential field. The computational complexity of the pertinent algorithms justify the applicability of the approach in real-time. Simulation results are included.

To derive the equations of motion for a multibody system using the Gibbs-Appell calculus – the partial derivatives of the Gibbs function G = 1/2 ∫ a2 dm with respect to the generalized accelerations equal the generalized forces-shows special advantages. Describing the kinematics with Jacobi matrices and local terms, these equations can be written in such a way that the partial derivations need not be performed explicitly. Kinetic effects of fast rotating driving devices attached to the moving links can be included in a similar way. Though an analytical formulation of the equations of motion is especially desirable with respect to its application for industrial robots, such a formulation becomes too extended and susceptible to errors for systems with more than 3 or 4 bodies. Therefore an approach is developed for tree structured robots with rotational or translational joints for calculating the Jacobi matrices and the local terms without employing any differentiation process. So it is possible to use the Gibbs-Appell method numerically in a recursive way e.g. for calculating the torques of the actuators of a robot with 6 or more degrees of freedom for a given motion.

The algorithms of inverse kinematics based on optimality constraints have some problems because those are based only on necessary conditions for optimality. One of the problems is a switching problem, i.e., an undesirable configuration change from a maximum value of a performance measure to a minimum value may occur and cause an inverse kinematic solution to be unstable. In this paper, we derive sufficient conditions for the optimal solution of the kinematic control of a redundant manipulator. In particular, we obtain the explicit forms of the switching condition for the optimality constraintsbased methods. We also show that the configuration at which switching occurs is equivalent to an algorithmic singularity in the extended Jacobian method. Through a numerical example of a cyclic task, we show the problems of the optimality constraints-based methods. To obtain good configurations without switching and kinematical singularities, we propose a simple algorithm of inverse kinematics.

Attaching the milking machine to the cow is the last remaining major repetitive task that the worker in a modern milking parlour has to perform. Several groups of research workers are developing robotic systems for this purpose. The task for the robot of locating the cow's teats and attaching the machine is complicated by morphological differences between cows and the need to allow the cow freedom to move during the operation. This paper reviews the progress that has been made.