In this paper, the use of central pattern generators (CPGs) is examined for legged locomotion. In doing so, a mathematical model that has the ability to emulate arbitrary locomotion gaits is developed. A simple algorithm for encoding the characteristic gaits of bipeds, quadrupeds and hexapeds is presented.

Many space robotic systems would be required to operate in uncertain or even unknown environments. The problem of identifying such environment for compliance control is considered. In particular, neural networks are used for identifying environments that a robot establishes contact with. Both function approximation and parameter identification (with fixed nonlinear structure and unknown parameters) results are presented. The environment model structure considered is relevant to two space applications: cooperative execution of tasks by robots and astronauts, and sample acquisition during planetary exploration. Compliant motion experiments have been performed with a robotic arm, placed in contact with a single-degree-of-freedom electromechanical environment. In the experiments, desired contact forces are computed using a neural network, given a desired motion trajectory. Results of the control experiments performed on robot hardware are described and discussed.>

Preliminary results are reported from efforts to design and develop a robotic system that will accept and execute commands from either a six-axis teleoperator device or an autonomous planner or combine the two. Such a system should have both traded and shared control capability. A sharing strategy is presented whereby the overall system, while retaining positive features of teleoperated and autonomous operation, loses its individual negative features. A two-tired shared control architecture is considered here, consisting of a task level and a servo level. Also presented is a computer architecture for the implementation of this system, including a description of the hardware and software.>

Dexterous hands offer a great deal of flexibility in grasping and manipulation. As such, it can be used as a powerful device for assembly. However, we have to guarantee stable behavior and good performance from the hand and so attention must be focused on control issues. In this paper we deal with the control of the JPL/STANFORD hand. We use kinematic relationships developed earlier and suggest dynamic models for the fingers. We then develop Linear Multivariable Feedback Control strategies which guarantee local stability for controlling one finger. We employ design methods in the frequency domain, based on pole assignment techniques. Controllers are designed for a simple dynamic model and implemented on one finger. Results are presented along with a discussion for future work.