Spacecraft missions such as spacecraft docking and formation flying require high precision relative position and attitude data. Although Global Positioining Systems can provide this capability near the earth, deep space missions require the use of alternative technologies. One such technology is the vision-based navigation (VISNAV) sensor system developed at Texas A&M University. VISNAV comprises an electro-optical sensor combined with light sources or beacons. This patented sensor has an analog detector in the focal plane with a rise time of a few microseconds. Accuracies better than one part in 2000 of the field of view have been obtained. This research presents a new approach involving simultaneous activation of beacons with frequency division multiplexing as part of the VISNAV sensor system. In addition, it discusses the synchronous demodulation process using digital heterodyning and decimating filter banks on a low-power fixed point DSP, which improves the accuracy of the sensor measurements and the reliability of the system. This research also presents an optimal and computationally efficient six-degree-of-freedom estimation algorithm using a new measurement model based on the attitude representation of Modified Rodrigues Parameters.

At the beginning of this master’s thesis the definition of types of robots using parallel kinematics are presented, its possibilities of usage and current prototypes are described. The second chapter focuses on the proposal of robot construction and sizing electric and non-electric components of robot hardware. Derivation of direct and inverse transform mechanisms with creating flowcharts of their algorithms are stated in the two following chapters. The state machine controlled from user interface is then programmed based on these flowcharts. At the end of the work, cable-driven robot positioning accuracy is evaluated and platform workspace, together with motion and electric parameters, are measured.