In programming robot manipulators to carry out a wide variety of tasks it would be desirable to create a CAD system in which these tasks can be programmed at the task level, leaving the fine-grained detail of path planning and collision detection to the system. This paper describes the theoretical background to such a system, by providing a model in which robot motions are represented using multivariate B-splines, a standard representation for free-form shapes in the CAD environment. The paper also describes algorithms which take this representation and apply it to collision detection and path-planning.

This paper considers the problem of controlling the motion of nonholonomic mechanical systems in the presence of uncertainty regarding the system model and state. It is proposed that a simple and effective solution to this problem can be obtained by first using a reduction procedure to obtain a lower dimensional system which retains the mechanical system structure of the original system, and then adaptively controlling the reduced system in such a way that the complete system is driven to the goal configuration. This approach is shown to be easy to implement and to ensure accurate motion control despite measurement and model uncertainty. The efficacy of the proposed control strategy is illustrated through computer simulations and preliminary hardware experiments with nonholonomic mechanical systems arising from both explicit kinematic constraints and symmetries of the system dynamics.

This paper presents a new recursive algorithm of robot dynamics based on the Kane's dynamic equations and Newton-Euler formulations. Differing from Kane's work, the algorithm is general-purpose and can be easily realized on computers. It is suited not only for robots with all rotary joints but also for robots with some prismatic joints. Formulations of the algorithm keep the recurrence characteristics of the Newton-Euler formulations, but possess stronger physical significance. Unlike the conventional algorithms, such as the Lagrange and Newton-Euler algorithm, etc., the algorithm can be used to deal with dynamics of robots containing closed chains without cutting the closed chains open. In addition, this paper makes a comparison between the algorithm and those conventional algorithms from the number of multiplications and additions.

This paper presents a kinematic analysis and design characteristics of an in-parallel manipulator developed for the probing task application that requires high precision, active compliance, and high control bandwidth. The developed manipulator is a class of six-degree-of-freedom in-parallel platforms with 3 PRPS (prismatic-revolute-prismatic-spherical joints) chain geometry. The main advantages of this manipulator, compared with the typical Stewart platform type, are the capability of pure rotation generation and the easy prediction of the moving platform motion. The purpose of this paper is to develop an efficient kinematic model which can be used for real-time control and to propose systematic methods to design the manipulator considering workspace, manipulability, resistivity, singularity, and the existence conditions of the forward kinematic solution. Particularly, we propose a new method for checking the singularity of the parallel manipulator using the translational and rotational resistivity measures. A series of simulation are carried out to show kinematic characteristics and performance of the manipulator mechanism. A prototype manipulator was built based on the kinematic analysis results.

The paper considers the influence of external forces on the behaviour of a redundant manipulator. It is assumed that the forces can act anywhere on the body of the manipulator. First, the equivalent generalized forces in the task space and the null space are defined and several special manipulator configurations regarding the equivalent forces and torques are identified. Next, two measures for the quantification of the influence of external forces on the task space are proposed. These measures are then used in the control algorithm to minimize the influence of external forces on the task space position accuracy. The control is based on the redundancy resolution at the acceleration level and the gradient projection technique. Improvement of the position accuracy is illustrated using the simulation of a four link planar manipulator.

Singularity of a robot manipulator is one of the obstacles that influences its capabilities. This paper discusses constrained and allowable rotational motion resulting from lost translational freedom when the robot is singular. A convenient method and simple and clear expression to determine the allowable rotational axes and the subspace that they form, under Jacobian singularity, is analyzed and presented. Different configurations, reciprocal screws, and subspaces of allowable-rotational-axes are derived in a case study involving a classic robot. The result is useful in applications involving robot path planning in task space as it extends the usable workspace of rotational axes.

Transpose Jacobian-based controllers represent an attractive approach to robot control in Cartesian space. These controllers attempt to drive the robot end-effector posture to a specified desired position and orientation without solving either the inverse kinematics nor computing the robot inverse Jacobian. A wide class of transpose Jacobian-based regulators obtained from the energy shaping plus damping injection technique is analyzed in this paper. Our main theoretical contribution is the introduction of a novel analysis which does not invoke any assumption on Jacobian singularities to ensure local asymptotic stability for a family of nonredundant robots. The performance of four transpose Jacobian-based regulators is illustrated via experimental tests conducted on a direct-drive vertical arm.

Most of the time, the construction of legged robots is made in an empirical way and the optimization of the mechanical structure is seldom taken into account. In order to avoid spending time and money on the construction of many prototypes to test their performance, a CAD tool and a methodology seem to be necessary. In this way it will be possible to optimize on one hand the kinematic structure of the legs, on the other hand the gaits which will be used by the future robot. Thus, we have developed a methodology to design walking structures such as quadrupeds and bipeds, to simulate their dynamic behavior and analyse their performances. The feet/ground interaction is one of the major problem in the context of dynamic simulation for walking devices. Thus, we focus here about the phenomenon of contact. This paper describes a general model for dynamic simulation of contacts between a walking robot and ground. This model considers a force distribution and uses an analytical form for each force depending only on the known state of the robot system. The simulation includes all phenomena that may occur during the locomotion cycle: impact, transition from impact to contact, contact during support with static friction, transition from static to sliding friction, sliding friction and transition from sliding to static friction. Some examples are presented to show the use of this contact model for the simulation of the foot-ground interaction during a walking gait.

This paper proposes a novel hierarchical multi-layer decision tree for representing reactive robot navigation knowledge. In this representation, the perception space is decomposed into a hierarchical set of worlds reflecting environments which are homogeneous in nature and which vary in complexity in an ordered manner. Each world is used to produce a corresponding decision tree which is trained incrementally. The instantaneous perception of the robot is used to select an appropriate rule from the decision tree and a sequence of rule activations form the complete trajectory. The ability to keep the knowledge complexity manageable and under control is an important aspect of the technique.

In this paper, a method is proposed for dynamic balancing of hexapods for high-speed applications. The kinematic structure of the hexapod is based on the parallel mechanism. For high-speed applications, hexapod dynamics is the dominant factor, and dynamic balancing becomes very important. The proposed method is aimed at minimizing the changes in the hexapod inertia over the workspace by utilizing the tool holder attached to the hexapod's end-effector as a counterweight.

The question of control and stabilization of flexible space robots is considered. Although, this approach is applicable to space robots of other configurations, for simplicity, a flexible planar two-link robot, mounted on a rigid floating platform, is considered. The robotic arm has two revolute joints and its links undergo elastic deformation in the plane of rotation. Based on nonlinear inversion technique, a control law is derived for controlling output variables describing the position and orientation of the platform and the joint angles of the robot. Although, the inverse controller accomplishes reference trajectory tracking, it excites the elastic modes of the arm. For the vibration suppression, three different stabilizers are designed. Using linear quadratic optimal control theory, a composite stabilizer for stabilization of the rigid and flexible modes and a decoupled flexible mode stabilizer are designed for regulating the end point of the robot to the target point and vibration suppression. Stabilization using only elastic mode velocity feedback is also considered. For large maneuvers, first the inverse controller is active, and the stabilizer is switched for regulation when the motion of the robot lies in the neighborhood of the terminal equilibrium state. Simulation results are presented to show that in the closed-loop system including the inverse controller and each of the stabilizers, trajectory tracking and stabilization of elastic modes are accomplished.