We synthesize an adaptive motion control law for a free-flying robot with no external forces or moments. The basic idea is to make use of the articulated part of the space robot to control the position and orientation of the end-effector in an inertial frame. The inertia parameters for the robot end-effector and load are assumed to be a priori unknown. The articulated-body model is linear in the unknown parameters, so that an adaptive control law is developed. A novel feature of our approach is that the parameter estimates are obtained using momentum integrals only. In addition, we use unit quaternions to represent orientation errors. The stability properties of the adaptive control law is shown using Lyapunov stability theory. Computer simulations of an example 12 degrees of freedom space robot system are presented.

Contact between free-flying space robots, and the minimization of the impulse at contact are studied. A general approach for modeling systems with a moving base is presented. In particular, the formulation of the dynamical equations of motion for a space-based manipulator system with external applied forces are considered. The new equation of motion is then used to derive a dynamical contact model. Unlike previous approaches, the analysis takes into account both relative translational and rotational motions between contacting bodies. An analysis of the dynamical contact model reveals that the impulse at contact could be minimized by the optimization of a scalar cost function. Two approaches to the Cartesian space planning problem for space-based systems are discussed. A joint space planning strategy that achieves both trajectory tracking and impact minimization is proposed. Simulation results for a fifteen-degree-of-freedom (DOF) space robot are presented.>

A computational scheme is presented for the implementation of passivity-based controllers for serial and graph structured manipulators. A special method of incorporating feedback improves the computational efficiency by allowing the designer to base the control on the passivity properties of the entire manipulator. Sufficient conditions are presented to guarantee trajectory tracking of the system. Example controllers and experimental results are presented.>

The authors present a novel adaptive control method for space-based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. They begin with a partitioning of the fifteen-degree-of-freedom system dynamics into two component: a nine-degree-of-freedom invertible portion and a six-degree-of-freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion of the system consists of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded but unpredictable. This portion of the system consists of the position of the robot's base and the position of the reaction wheels. Simulation results are presented on a space-based robot with five revolute joints and one prismatic joint.>

A control method is presented that achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. The 15-degree-of-freedom (DOF) system dynamics are divided into two components: a 9-DOF invertible portion and 6-DOF noninvertible portion. A controller is then designed to achieve trajectory tracking of the invertible portion of the system, which consists of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded but otherwise unspecified. This portion of the system consists of the position of the robot's base and the position of the reaction wheels. A simulation is presented to demonstrate the effectiveness of the controller. A quadratic polynomial is used to generate the desired trajectory to illustrate the trajectory tracking capability of the controller.>

A dynamic world model is presented on which all planning, sensing, and control functions are based. A planning system that specifies how tasks are to be performed and the method used for sensing the state of the task are presented. The objectives of the control law and the algorithm used in the controller are given. Practical considerations are addressed, and some important details, such as the use of the null task, are explained. An example task of opening a door is examined.>

Several algorithms used for the calibration of a manipulator are presented. The calibration includes the estimation of friction coefficients, position sensor calibration, and the motor torque constants. The model used for compensation of the gearing effects is described. The results of application of these algorithms to the PUMA 560 manipulator are presented.>

The authors have coined the term teleautonomous to describe methods for producing intelligent action at a distance. Teleautomation goes beyond autonomous control in that it blends in human intelligence and action as appropriate. It goes beyond teleoperation in that it incorporates as much autonomy as is possible or reasonable. A novel approach for solving one of the fundamental problems facing teleautonomous systems is discussed in detail: the need to overcome time delays due to telemetry and signal propagation. Concepts called time and position clutches are introduced; these allow the time and position frames, respectively, between the local user control and the remote device being controlled to be desynchronized. The design and implementation of these mechanisms lead to substantial telemanipulation performance improvements, including the novel result of improvements even in the absence of time delays. The controls also yield a simple protocol for handoffs of the control of manipulation tasks between local operators and remote systems.>

A novel algorithm for the adaptive control of a robot manipulator which may contain closed kinematic loops is described. The algorithm identifies the mass properties of each link and the viscous friction coefficients for each joint of the manipulator. It is similar to the Newton-Euler inverse dynamics algorithm and, hence, obtains its computational efficiency through the recursive nature of the algorithm. Improved computational efficiency is achieved by eliminating the need to compute the constraint forces. Only inertial and gravitational forces are actually computed by the algorithm. Simulation results are presented.>

An approach to the problem of finding the minimum number of inertial parameters of the robot manipulator dynamic equations of motion is presented. Based on the energy difference equation, it is equally applicable to serial-link graph-structured manipulators. The authors prove that the minimum number of parameters can be obtained directly from an energy difference equation rather than the dynamic equations of motion. They present a method for the identification of the minimum number of basis vectors which span the vector space containing the components of inertial parameters present in the equations of motion. Simulations are presented and the method is evaluated. The method is conceptually simple, computationally efficient and easy to implement. In particular, the manipulator kinematics and the joint positions and velocities are the only inputs to the algorithm.>

An adaptive controller is presented for the coordinated motion control of two manipulators handling an object of unknown mass. Global convergence in tracking of both position and internal force trajectories of the object is proved, assuming perfect models for both manipulators. The computational algorithm is similar to the Newton-Euler inverse dynamics algorithm with complexity linear in the number of links in the manipulators. A significant feature of the control method is that both manipulators use the identical computational algorithm. Thus, the concept of master/slave relationship between the two manipulators is avoided. Two simulations are presented. The first assumes an ideal model for each manipulator. As expected, the controller is stable and provides excellent tracking ability of the manipulator. The second simulation investigates the effects of modeling errors in the mass properties of each arm. The position trajectories track very close to their desired values; however, they never completely converge.>

A novel algorithm is described for the adaptive control of a robot manipulator which may contain closed kinematic loops. The algorithm identifies the mass properties of each link and the viscous friction coefficients for each joint of the manipulator. It is similar to the Newton-Euler inverse dynamics algorithm and hence obtains its computational efficiency through the recursive nature of the algorithm.>

An algebra is defined for use in problems of manipulator kinematics. With this algebra, one can program the solution to the kinematics in position problems, and use this same program to solve the kinematics problems in velocity and acceleration. The inverse kinematics part of the program can be used to obtain any order time-derivative of the joint positions. Some of the properties of the algebra are shown and functions of the elements of the algebra are defined. The solution to the forward and inverse kinematics problem is presented, and the use of the Ada programming language is discussed.>

As a result of recent advances in artificial intelligence, human cognitive modelling, autonomous systems and telerobotics, there is an opportunity to broaden our concepts of technology for projecting action at a distance. We draw on these advances to develop a conceptual and architectural framework that enables efficient projection in time and space of intermingled manipulation and cognition tasks. Where AI-based autonomous systems have previously been concerned with human supervisory intervention primarily at a cognitive level, we add methods for rendezvous, capture and rehandoff of embedded manipulation tasks. Where telerobotics has been concerned with the projection of sensory-motor manipulation, we add the projection of cognitive processing. Thus extended, the two technologies mirror one another and merge into one of "tele-autonomous systems". We introduce notions of how the sensory, cognitive and motor functions of tele-autonomous systems can be factored and transferred back and forth between human and machine. We illustrate how the times to complete tele-autonomous tasks can be reduced through time and space constraint relaxations effected through simple controls: We employ the concepts of forward simulation and predictor display, augmented by "time and position clutches", "time ratio controls" and "time brakes", to control the resulting manipulation paths and event transitions. We sketch some generic architectural and human interface implications of these methods. Finally, we describe our environment for exploring these methods and the results of some recent experiments.

A new algebra is defined for use in problems of manipulator kinematics. With this algebra the solution to the inverse kinematics problem can be solved for any time derivative of the joint position using the same program by simply changing the order of the algebra. An example Ada program is used for illustration.

It is recognized that three different types of mechanisms are required to model a manipulator in most applications. Those are the serial-link, tree structured, and graph structured mechanisms. The model for each type of mechanism is presented in both the recursive and nonrecursive formulations utilizing the same notation throughout. The result is a modeling methodology which clearly shows the relationships between the models of the different types of mechanisms and formulations.