Harold L. Alexander

Experiments on the Control of a Satellite Manipulator

Automation is becoming increasingly important to the exploration and utilization of space. Space-based robotic systems will provide efficient and inexpensive means to work in space. The dynamic control of space robots presents unique challenges, partly due to the robot’s lack of a fixed base.

State estimation for distributed systems with sensing delay

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

Experiments in Teleoperator and Autonomous Control of Space Robotic Vehicles

This paper presents a program of research embracing teleoperator and automatic navigational control of freely-flying satellite robots. Current research goals include developing visual operator interfaces for improved vehicle teleoperation; determining the effects of different visual interface system designs on operator performance; and achieving autonomous, vision-based vehicle navigation and control. This research program combines virtual-environment teleoperation studies and neutral-buoyancy experiments using a space robot simulator vehicle currently under development. Visual-interface design options under investigation will include monoscopic versus stereoscopic displays and cameras, helmet-mounted versus panel-mounted display monitors, head-tracking versus fixed or manually steerable remote cameras, and provision of vehicle-fixed visual cues, or markers, in the remote scene for improved sensing of vehicle position, orientation, and motion. Autonomous-control research currently focuses on the development of the neutral-buoyancy vehicle and vision-based sensing systems required to support future automatic vehicle control experiments.

Vision navigator for free-flying robots

A vision technique applicable to the sixth degree-of-freedom navigation of free-flying space robots is discussed. The technique consist of a feature finder which matches points in the environment with image locations and a recursive estimator based on the extended Kalman filter which uses measurements of the image locations to update the state estimate recursively. Experimental results are presented which demonstrate the convergence and state tracking properties of the system. Results include the finding that a vision navigator can be implemented with current off-the-shelf equipment if a sufficiently simple object in the environment acts as the navigation target.

Robotic control of sliding object motion and orientation

The models and control strategies presented allow repositioning an object that slides on a surface or between the jaws of a parallel-jaw gripper. Such techniques can save the need to pick up payloads for moving, or to deposit a gripped object for grasp modification. Precisely controlling a sliding objects position and orientation requires a model of its motion that recognizes both imposed motion and frictional forces. This paper presents an analysis of sliding-object motion that is based in part on Masons quasistatic integral for frictional force (1985). Masons model is extended to create linearized models of both straight-line and curvilinear sliding motion that permit deriving feedback control strategies based on purely proportional feedback of position errors, relative to reference trajectories. These controllers are very robust due in part to the simplicity of the model and of the physical plant, despite the nonlinearity of the true plant dynamics. Application of integral control is straightforward, in order to correct for modeling errors or disturbance forces, and control saturations are suggested to ensure stability even for large errors. Closed-loop control simulations confirm the effectiveness and robustness of these feedback control strategies.

Experiments in vision-based control of a neutrally buoyant free-flyer

The Laboratory for Space Teleoperation and Robotics is developing a neutrally-buoyant robot for research into the automatic and teleoperated (remote human) control of unmanned robotic vehicles for use in space. The goal of this project is to develop a remote robot with maneuverability and dexterity comparable to that of a space-suited astronaut with a manned maneuvering unit, able to assume many of the tasks currently planned for astronauts during extravehicular activity (EVA). Such a robot would be able to spare the great expense and hazards associated with human EVA, and make possible much less expensive scientific and industrialization exploitation of orbit. Both autonomous and teleoperated control experiments will require the vehicle to be able to automatically control its position and orientation. The laboratory is developing vision-based vehicle navigation system that works by tracking features in video images from cameras mounted on the vehicle and trained at a special target fixed in the environment. The methods are adaptable to a variety of video-based tracking systems, and are based on a linearized vision model, receiving as inputs image feature coordinates at each time step This paper includes a description of the underwater vehicle and the vision system.

Robot free-flyers in space extravehicular activity

The Laboratory for Space Teleoperation and Robotics is developing a neutrally buoyant robot for research into the automatic and teleoperated (remote human) control of unmanned robotic vehicles for use in space. The goal of this project is to develop a remote robot with maneuverability and dexterity comparable to that of a space-suited astronaut with a manned maneuvering unit, able to assume many of the tasks currently planned for astronauts during extravehicular activity (EVA). Such a robot would be able to spare the great expense and hazards associated with human EVA, and make possible much less expensive scientific and industrialization exploitation of orbit. Both autonomous and teleoperated control experiments will require the vehicle to be able to automatically control its position and orientation. The laboratory has developed a real-time vision-based navigation and control system for its underwater space robot simulator, the Submersible for Telerobotic and Astronautical Research (STAR). The system, implemented with standard, inexpensive computer hardware, has excellent performance and robustness characteristics for a variety of applications, including automatic station-keeping and large controlled maneuvers. Experimental results are presented indicating the precision, accuracy, and robustness to disturbances of the vision-based control system. The study proves the feasibility of using vision-based control and navigation for remote robots and provides a foundation for developing a system for general space robot tasks. The complex vision sensing problem is reduced through linearization to a simple algorithm, fast enough to be incorporated into a real-time vehicle control system. Vision sensing is structured to detect small changes in vehicle position and orientation from a nominal positional state relative to a target scene. The system uses a constant, linear inversion matrix to measure the vehicle positional state from the locations of navigation features in an image. This paper includes a description of the underwater vehicles vision-based navigation and control system and applications of vision-based navigation and control for free-flying space robots. Experimental results from underwater tests of STARs vision system are also presented.

Experiments in tele-operator and autonomous control of space robotic vehicles

A program of research is presented that embraces teleoperator and automatic navigational control of freelyflying satellite robots. Current research goals include developing visual operator interfaces for improved vehicle teleoperation studying the effects of different visual interface system designs and achieving autonomous visionbased vehicle navigation and control. This research program combines virtual-environment teleoperation studies with neutral-buoyancy experiments using a space robot simulator vehicle that is currently under development. Visualinterface design variables include monoscopic versus stereoscopic displays and cameras helmet-mounted versus panelmounted display monitors head-tracking versus fixed or manually steerable remote cameras and provision of vehiclefixed visual cues or markers in the remote scene for improved sensing of vehicle position orientation and motion. Autonomous-control work concentrates on developing the neutral-buoyancy vehicle and the vision-based sensing systems that will support automatic vehicle control experiments.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.