A local-remote telerobot control system is described which is being developed for time-delayed groundremote control of space telerobotic systems. The system includes a local site operator interface for interactive command building and sequencing for supervised autonomy and a remote site: the Modular Telerobot Task Execution System (MOTES), to provide the remote site task execution capability. The local site system also provides stereo graphics overlay on video with interactive update of the remote environmental model. The operator selects objects in the environment to interact with and skill types to specify the tasks to be performed, such as grasping a module or opening a door.

Two types of computer boards incorporating recently developed VLSI fuzzy inferencing chips have been developed to support the addition of qualitative reasoning capabilities to the real-time control of robotic systems. The design and operation of these boards are first reviewed and their use, in conjunction with our proposed Fuzzy Behaviorist approach, is discussed. This approach uses superposition of elemental sensor-based behaviors expressed in the Fuzzy Sets theoretic framework, to emulate "human-like" reasoning inrobotic systems.

Using a functional architecture such as the NASA/NIST Standard Reference Model for Telerobot Control System Architecture (NASREM) to implement specific applications is helpful because much of the work resides in the infrastructure and the infrastructure is the same for all applications. Rather than recreating this infrastructure, our approach is to develop the additional 20% of the code which tailors the infrastructure for the specific application. This paper describes the process by which a system based on NASREM is developed.

The virtual passive control approach has recently been shown to be an effective technique for robust compensation of linear as well as nonlinear systems, when the system is open-loop stable and behaves as a block second-order plant. Mechanical systems as well as current space structure designs possess this property whereby inertia, damping and stiffness parameters characterize the dynamics.

Implementation of such controllers using digital systems may lead to instability, however, unless discretization issues are addressed. This paper presents a discrete-time representation of the Virtual Passive Approach and develops the robust controller structure for linear systems. The algorithm is then applied to a model of an actual experimental testbed; the test article is a ten-bay truss structure located at NASA Langley's Spacecraft Dynamics Branch. Results illustrate the robustness properties of the algorithm and expose issues which need to be addressed in future research activities.

Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the priority. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem. The fuzzy controller was tested on a mobile robot system in an indoor environment and found to perform satisfactorily despite having crude sensors and minimal sensory feedback.

Motion Planning and control of mobile vehicles with nonholonomic constraints are in their infancy. A systematic approach for modeling and base; motion control of a mobile vehicle is presented. A nonlinear coordinate transformation that takes into account the complete dynamics with nonholonomic constraints is used in order to obtain a linear system in space coordinates. An input-output feedback linearization inner loop is subsequently designed to transform this system into a linear-point mass system in the coordinates corresponding to the control objectives. A rigorous yet simple approach to motion planning through optimization techniques is presented for these mobile vehicles. The resulting Cartesian trajectory generated from the motion planning algorithm is employed as the reference trajectory in the outer loop, which is designed based on a Lyapunov function candidate. The net result is a base motion controller that gives capabilities to these mobile vehicles not only for tracking a Cartesian trajectory but also to achieve a desired final orientation (docking angle).

In this paper, a joint space dynamic control scheme with an adaptive identifier is proposed for free-flying space robots. The control in Cartesian space poses a measurement problem which is critical from a point of view of implementation. In order to overcome this problem, a joint space control is developed. An inverse kinematics algorithm is proposed so as to control free-flying space robots in joint space. Since the inverse kinematic solutions for space robots depend on the dynamic parameters as well as the kinematic.parameters, the accurate estimation of all the unknown parameters is essential to make joint space control possible. Therefore, an off-line adaptive parameter identification is performed for free-flying space robots. Simulation results are given to show the validity and the effectiveness of the presented adaptive identification and dynamic control scheme.

This paper describes an adaptive control system for an articulated robot with n joints carrying a variable load. The robot is a complex nonlinear time-varying MIMO plant with dynamic interaction between its inputs and outputs. However, the design of the control system is relatively straightforward and does not require any prior knowledge about the plant. This is because the control system is based on using neural networks which can capture the dynamic characteristics of the plant automatically. Three neural networks are employed in total, the first to learn the dynamics of the robot, the second to model its inverse dynamics and the third, a copy of the second neural network, to control the robot.

This work concerns the class of wheeled mobile robots with single axis front steering. Because of the relatively low speed of these vehicles their dynamic properties have little effect on their path tracking behaviour. Their motion is, moreover, on a flat environment and can be assumed two dimensional.

The kinematics of motion of such a vehicle can be utilized for design of control strategies for maintaining path following stability. In this paper, optimal control technique is implemented to such a system. First, the state space equations governing the motion are derived. The orientation error and the offset from a path form the states and the steering angle is the control input to the system. An optimal controller to minimize the two errors and the steering angle is then sought. The conditions for the existence of the feedback matrix are discussed. The controller structure is defined in terms of the forward speed of the vehicle and, thus, has the advantage of being flexible for speed changes. Numerical illustrative examples, however, demonstrate that variation of the speed has no effect on the controller structure.

This paper considers some problems concerning the motion and the control of large robots. The problem arises when highly nonuniform motion is required. It results in too strong dynamic loads and the robot cannot operate successfully. The solution is found in the introduction of redundancy in the form of parallel degrees of freedom. Kinematics of such a system follows the distributed positioning concept. The control scheme is developed for a one-dimensional redundant robot.