Automated methods are developed to classify a robot's kinematic type and select an appropriate library inverse-kinematic solution based on this classification. These methods automatically generate DenavitHartenberg joint frame parameters, given any frame representation that can mathematically be represented as a homogeneous transformation.

To reduce the number of closed-form inverse-kinematics solutions required for a broad class of serial robots, additional methods account for differences in robot zero state, base frame location, and joint polarity. Further generalization results from using joint frame decoupling to map lower degree-of-freedom robots into the inverse-kinematics solutions of higher degree-offreedom robots.

The paper describes a newly developed three-dimensional computer animation system to be used for creating motion programs for a set of actors. The animation package includes a language for describing spatial motion of bodies, as well as an interactive tool to be used for assigning geometrical attributes to them and for guiding and visualizing the play-back of motion programs. One of the main uses of the package is robot programming and motion simulation. A geometrical modeller, which is a an aid in creating the models of animated bodies, is also described.

This paper discusses suitable mechanisms and functions of a mobile microrobot from the point of view ofscale effects. Several assumptions are made using animalscaling. A large scale model is shown to demonstrate these mechanisms. Moreover, microsized models have been built on silicon wafers by using polysilicon as rigidplates and polyimide as elastic joints. The results showthat suitable mechanisms and functions may be different from those of a conventional robot.

In the field of multifingered mechanisms the control/command problem is mainly a problem o1 coordination. The problem is not only to coordinate joints of a chains but also to coordinate the different chains together.

This paper presents a general and efficient method for implementing the control/command of such systems, taking into account the force distribution problem. To solve this problem it is necessary to pay great attention to dynamic effects. To do this, we broke down the Inverse Dynamic Model (I.D.M.) problem into two main levels; One level is devoted to I.D.M. computation; it can be called the Finger Level (F.L.). As we wanted to divide up the work to be done as much as possible, we subdivided the Finger Level according to the number o1 kinematic chains. In addition, we considered a second level, the Coordinator. This level has to control all the chains using the Fingers-to-Object-Interaction Model (F.O.LM.).

Next, we will also introduce new grasping systems: Polyvalent Gripper Systems (P.G.S). There are a new solution to multicomponent assembly problems. As they can be equipped with several multifingered mechanisms, they can also use the control/command scheme.

It has been experimentally verified that the jerk of the desired trajectory adversely affects the performance of the tracking control algorithms for robotic manipulators. In this paper, we investigate the reasons behind this effect, and state the trajectory planning problem as an optimization problem that minimizes a norm of joint jerk over a prespecified Cartesian space trajectory. The necessary conditions are derived and a numerical algorithm is presented.

An algorithm for the inference of the external behaviour model of an automaton is given. It uses a sequential learning procedure based on induction-contradiction-correction concepts. The induction is a generalization of relationships between automaton state properties, and the correction consists in a more and more accurate discrimination of the automaton state properties. These properties are defined from the input/output contradictory sequences which are discovered after the observed contradictions between successive predictions and observations.

The paper focuses on the problem of trajectory planning of multiple coordinating robots. When multiple robots collaborate to manipulate one object, a redundant system is formed. There are a number of trajectories that the system can follow. These can be described in Cartesian coordinate space by an nth order polynomial. This paper presents an optimisation method based on the Genetic Algorithms (GAs) which chooses the parameters of the polynomial, such that the execution time and the drive torques for the robot joints are minimized. With the robot's dynamic constraints taken into account, the pitimised trajectories are realisable. A case study with two planar-moving robots, each having three degrees of freedom, shows that the method is effective.