Positioning uncertainty becomes a major problem for position-control-based robots when operating in contact with the environment. Inaccuracy in positioning parts or inadequate information about part placement has traditionally been addressed through accurate fixturing, calibration and robot programming. Impedance control provides a mechanism for using the reaction forces and torques at the end effector to compensate for positioning uncertainty. Redundant manipulators have greater manipulability than nonredundant manipulators thus facilitating the implementation of more complex tasks, and making it possible to also avoid collisions by taking advantage of the redundancies. Handling positioning uncertainty while simultaneously avoiding collisions are solved by using the generalized impedance control algorithm developed in this study. This was successfully demonstrated on the 7 degree-of-freedom redundant Robotics Research Corporation K1207i manipulator.

Presents a methodology which allows an autonomous agent i.e., a mobile robot, to learn and build maps of its operating environment by relying only on its range sensors. The maps, described with respect to the robot's inertial frame, are developed in real time by correlating robot position and sensory data. This latter feature characterizes part of the uniqueness of the authors' approach. These maps are topologically isomorphic to the maps created for the same room(s) by humans. The methodology exploits the principle of self-organization, implemented as an artificial neural network module which processes incoming sensor range data. The generation of environmental maps can be visualized as an elastic string of neurons whereby every neuron represents a finite portion of the physical world. This elastic string stretches dynamically so as to take on the shape of the environment, a unique characteristic of the authors' methodology. In this respect, the neural net provides a discretized representation of the "continuous" physical environment as the latter is seen through the robot's own sensors. Experiments, focused on indoor applications, have successfully demonstrated the ability of a robot to build maps of geometrically complex environments. The results presented in this paper, compared with the authors' earlier efforts, show significant improvement in that every single sensor data point contributes equally to the location of the neurons of the spatial map at the end of the learning process. This is important because the authors wish to minimize the effect of the order in which data points are processed.

A methodology is presented whereby a neural network is used to learn the inverse kinematic relationship for a robot arm. A two-link, two-degree-of-freedom planar robot arm is simulated, and an accompanying neural network which solves the inverse kinematic problem is presented. The method is based on Kohonen's self-organizing mapping algorithm using a Widrow-Hoff-type error correction rule as introduced by H. Ritter et al. (1988, 1990). The authors have specifically addressed a number of issues associated with the inverse kinematic solution, including the occurrence of singularities and multiple solutions. Simulation results for a planar two-degree-of-freedom arm provide evidence that this approach is successful. The approach is a significant improvement over other neural net approaches documented in the literature.>

The use of impedance-controlled robots for simulating inertial loading effects is investigated. This is specifically of interest for replicating manipulation tasks occurring in a gravityless environment on the ground where gravitational forces exist. Results based on a simplified linear robot model are obtained. A description is given of some of the limitations as well as some necessary conditions for maintaining stability during manipulative interactions between a robot carrying out a task and a robot providing inertial response on a manipulated payload.>

An advanced method for tracking the three-dimensional motion of bodies is presented. This system, which is presently being used for human motion tracking, has the potential for dynamically characterizing robot motion and also provides a means for facilitating robot endpoint control. Three rotating planes of laser light, fixed and moving photovoltaic diode targets, and a pipelined architecture composed of analog and digital electronics are used to locate multiple targets whose number is only limited by available computer memory. Data collection rates are a function of the laser scan rotation speed and are selectable up to 480 Hz. The tested performance on a preliminary prototype designed for 0.1-in. accuracy at a 480-Hz data rate includes a resolution of 0.8 mm, a repeatability of +or-0.636 mm, and an absolute accuracy of +or-2.0 mm within an eight cubic meter volume with all results applicable at the 95% level of confidence along each coordinate direction. The system can be used to reduce XYZ target position data to body angular orientation which, for this first prototype, ranges in accuracy from +or-0.5 degrees to +or-1 degrees . Moving targets can be tracked at speeds exceeding 1 m/s with signal integrity tested but not limited to 25-Hz motions.>

General guidelines for analyzing friction at the joints are discussed. It is shown that friction can be related to the joint coordinates and their first and second time derivatives. The resulting extended robot dynamics formulation is investigated as it applies to the inverse and forward robot dynamics problems. The analytical dependency of Coulomb friction on joint interactions is explicitly examined. As an illustration of friction effects in transmissions, the friction in harmonic drives is considered and a method is developed for its evaluation. The quantitative characterization of several specific cases is provided. The study is significant for the design and control achieving of high-speed precision robot motion.>

One aspects of the control of multifingered hands is discussed, nearly inverse kinematics. For a serial-link manipulator with a multifingered hand attached to its distal link, the inverse kinematics of the hand and of the manipulator can be treated separately. The inverse kinematic solution for a three-fingered, nine-degree-of-freedom hand is described. The solution presented for the general configuration of the hand is unique and unambiguous; however, this is not the case for certain joint configurations, which are identified.>

Equations were developed which describe the motion of a robot manipulator which incorporates both structural and joint flexibility. The emphasis was on the dynamic model of a one-link flexible manipulator to show how critical it is to incorporate joint flexibility and to demonstrate the significance of cross coupling among state variables for small deflection. A set of decoupled dynamic equations was obtained based on the assumed-mode method and on orthogonality relations. By comparison to a model which incorporates cross coupling, it was shown that it is sufficiently accurate to use the decoupled dynamic equations for small joint and structural deflections. Simulations of varying joint stiffness characteristics indicates that there is no rigid mode for the flexible joint system. As such, both structural and joint flexibility must be considered in the analysis and control of such systems.>

Robot design and evaluation requires an extensive analysis of the nature and the quantitative interrelations of the dynamic factors that govern the operation of a manipulator. Coulomb friction is an inherent phenomenon in devices with moving parts. In multi-degree of freedom mechanical devices, Coulomb friction causes highly nonlinear coupling of the corresponding differential equations of motion. Furthermore, the presence of Coulomb friction is responsible for motion inaccuracies. This paper addresses the fundamental issues associated with Coulomb friction and investigates their consequences on design and performance considerations. Moreover, it develops the reasoning that permits the incorporation of Coulomb friction into the study of the dynamic response of a robot. Within this framework, a recursive approach that reveals the motion progress of a manipulator may be developed for digital simulation-oriented applications, implementation of the properties and principles discussed therein, may help uncover critical aspects of a manipulator's functionality and suggest ways for design improvements.

A system which automatically locates a part assembly task in a robot's workspace is described in this paper. The system determines the manipulability of a robot at points during the assembly operation. The assumption is made that the location of the assembly task within the workspace that results in the highest manipulability for the robot is a locally optimal position for performing the assembly. A path from assembly point to assembly point is also calculated to ensure that all motions necessary to perform the assembly operation are possible. In addition, a comparison of a manipulator's ability to perform a specific assembly operation in different workspace regions may be displayed graphically. Examples of various placements of an assembly task in a workspace and the placements' corresponding manipulability ratings are given, along with a graphical display of the comparison of manipulability in the different workspace regions.

An advanced method of tracking the three-dimensional motion of bodies has been developed. This system has the potential of dynamically characterizing robot motion and facilitating their end-point control. Three rotating planes of laser light, fixed and moving photovoltaic diode targets, and a pipe-lined architecture of analog and digital electronics are used to locate multiple targets whose number is only limited by available computer memory. Data collection rates are a function of the laser scan rotation speed and are currently selectable up to 480 hz. The tested performance on a preliminary prototype designed for 0.1 in accuracy (for tracking human motion) at a 480 hz data rate includes a resolution of 0.8 mm (0.03 inches), a repeatability of ± 0.635mm (± 0.025 inches), and an absolute accuracy of ± 2.0mm (± 0.08 inches) within an eight cubic meter volume with all results applicable at the 95% level of confidence along each coordinate direction. The system can be used to reduce XYZ target position data to body angular orientation for this first prototype ranges from ± 0.5 to ± 1 degree. Moving targets can be tracked at speeds exceeding 1 m/s with signal integrity tested but not limited to 25 hz motions.