This paper describes the robotics facilities and associated research program of the Jet Propulsion Laboratory, lead center in telerobotics for the United States National Aeronautics and Space Administration. Emphasis is placed on evolution from teleoperation to remote System automation. Research is described in manipulator modelling and control, real-time planning and monitoring, navigation in outdoor terrain, real-time sensing and perception, human-machine interface, and overall System architectures. Applications to NASA missions emphasize robotic spacecraft for solar System exploration, satellite servicing and retrieval, assembly of structures, and surveillance. Applications to military missions include battlefield navigation, surveillance, logistics, command and control.

In this paper we develop a compilant system that permits robotic assembly of chamferless pieces. The idea is to absorb the positioning error between parts to be inserted by giving one of them a planar random movement. An actuator consisting of two axes (X and y) operated by an electromagnetic System is fitted to the work table; when its inputs are pseudo-random binary signais (P.R.B.S.) random motion is obtained. The trajectories of the actuator are analysed depending upon the P.R.B.S. parameters and a peg-in-a-hole assembly task is carried out. Experimental results show that large positioning errors can be compensated for chamferless insertions.

In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the System structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

The extraction of contour information from objects is essential for purposes of grasping and manipulation. We proposed that human haptic exploration of contours, in the absence of vision, would reveal specialized patterns. Task goals and intrinsic system capacities were assumed to constrain the breadth of processing and the precision with which contour is encoded, thus determining parameters of exploration and ultimately producing movement synergies or “contour exploration procedures.” A methodology for testing these assumptions is described, and the most frequently observed procedures are documented in Part 1. Part 2 will further analyze the procedures, test predictions, and develop implications of the research. The paper (2 parts) is novel in its study of human manipulative behavior from a robotic standpoint; it is thus of interest to robotics research workers interested in the long-term goals of robot manipulation and those interested in an anthropomorphic approach to robotics studies.

Based on the Lyapunov theory, a new principle was developed for synthesizing robot tracking control in the presence of model uncertainties. First, a general Lyapunov-like robust tracking concept is presented. It is then used as a basis for the control algorithm derived via a quadratic Lyapunov function constructed using a sliding mode function (based on the output error). Control synthesis is made in task-space, without any need for solving the inverse kinematics problem, i.e. one does not need to inver the Jacobian matrix. It is also shown that the tracking error becomes close to zero in a settling time which is less than a prescribed finite time. Simulation results are incorporated.

This paper presents a general method to identify the geometric parameters of robots. An algorithm is given to calculate the identifiable geometric parameters. The robot location and the tool location parameters are taken into account. The algorithm is generalized to tree structure robots. The problem of selecting the optimum robot configurations to be used during the identification is discussed and a solution is proposed.

Virtual reference is defined as the signal for a closed-loop System so that the response tracks the desired path perfectly. It is proposed to obtain a virtual reference signal suitable for a manipulator to track a predetermined trajectory using repetitive operations. Thus the algorithm ensures that the difference between the desired and the manipulator trajectories will become negligible as the number of operations approaches infinity if the manipulator is compensated for properly by local feedback. This algorithm uses a dual System to recursively improve the reference signal. Such a System has the advantage of being simple to design. The derivation of this algorithm is based on functional analysis. The effectiveness is confirmed by two experimental results.

The minimum-time motion of robot manipulators is solved by defining a suitable time history for the arm end-effector to traverse. As the planning is performed in the configuration space, the uniqueness of the proposed algorithm emerges from the combination of both cubic and quadratic polynomial splines. Furthermore, the highly efficient time optimisation procedure could be applied to local segments of each joint trajectory, leading to a significant reduction of the travelling time. In addition, the ability to perform a search in the work space is granted, exploiting all possible options for an optimum motion. The method proposed considers all realistic physical limitations inherent in the manipulator design, in addition to any geometric constraints imposed on the path. Simulation programs have been written, and results are reported for the Unimation PUMA 560 robot manipulator.

A robotic manipulator is usually a very complicated system whose dynamics is too complicated time consuming for real-time control. The authors propose general criteria for designing an ideal robot whose dynamics is very much simpler than that of the conventional one. In this paper, dynamic characteristics of an ideally designed robot are investigated. The design guidelines were applied to a 6-degree-of-freedom PUMA 560 robot. Based upon the design concept dynamic equations of the redesigned robot were derived. Utilizing these equations, dynamic characteristics of the redesigned robot are investigated with respect to the computation efforts required, variation of the inertia matrix, joint input torque chracteristics, and couplings between the joints. A detailed comparison study is also made between the redesigned and conventional robots.

This paper presents a simple identification method of the actual kinematic parameters for a robot with parallel joints. It is known that Denavit–Hartenberg's coordinate System is not useful for nearly parallel joints. In this paper, the coordinate frames are reassigned to model the kinematic parameter between nearly parallel joints by four parameters. The proposed identification method uses a straight ruler about 1 m long. A robot hand is placed by using a teaching pendant at the prescribed points on the ruler, and the corresponding error function is defined. The identified kinematic parameters, which make the error function zero, are obtained by the iterative least square method based on the singular value decomposition. In the compensation of joint angles, only the position is considered because the usual applications of robot do not require a precise orientation control.

By using very simple considerations related to the mechanical Lagrangian itself, one obtains a new general class of parameter adaptation algorithms for robot manipulators, which provides such approaches as PID adaptation schemes. These models could apply to random structural mechanical Systems, subject to the conditon that they are defined by Lagrangians.