Engineering topics
Publications and source records attributed to Fiorini, Paolo.
This paper describes an environment for the design, simulation and control of Internet-based force-relflecting telerobotc systems. We define these systems as using a segment of the computer network to connect the master to the slave.
This paper describes the approach followed in the design of a service robot for health care applications. Under the auspices of the NASA Technology Transfer program, a partnership was established between JPL and RWI, a manufacturer of mobile robots, to design and evaluate a mobile robot for health care assistance to the elderly and the handicapped. The main emphasis of the first phase of the project is on the development on a multi-modal operator interface and its evaluation by health care professionals and users. This paper describes the architecture of the system, the evaluation method used, and some preliminary results of the user evaluation.
This paper describes the architecture and performance of a PC-based controller for 7-DOF dextrous manipulators. The computing platform is a 486-based personal computer equipped with a bus extender to access the robot Multibus controller, together with a single board computer as the graphical engine, and with a parallel I/O board to interface with a force-torque sensor mounted on the manipulator wrist.
Method of planning motions of object to prevent collisions with other moving objects derived from concept of collision cones in relative-velocity space. Collision cones computed, then maneuvers chosen to avoid these cones. Method considered prototype of automated method of planning motions in diverse applications, including complex manufacturing tasks involving coordination of multiple robots and controlling land, air, and sea traffic.
This paper presents a new approach for robot motion planning in dynamic.
Within NASA's recent thrust for industrial collaboration, JPL (Jet Propulsion Laboratory) has recently established two technology cooperation agreements in the robotics area: one on virtual reality (VR) calibration with Deneb Robotics, Inc., and the other on redundant manipulator control with Robotics Research Corporation (RRC). These technology transfer cooperation tasks will enable both Deneb and RRC to commercialize enhanced versions of their products that will greatly benefit both space and terrestrial telerobotic applications.
This paper briefly describes an Advanced Teleoperator (ATOP) system and its control station where a variety of computer-based operator interface devices and techniques are integrated into a functional setting, accommodating a primary operator and secondary operators. Computer graphics is a key operator interface component in the control station where new types of manual interface devices also are employed. The results of some generic and applications task experiments are summarized, including the performance of a simulated remote satellite servicing task, carried out under four to eight seconds communications time delay, using satellite TV and Internet computer communication links. In conclusion, the paper highlights the lessons learned so far,.
Prototype artificial neural network, implemented in software, identifies phases of telemanipulator tasks in real time by analyzing feedback signals from force sensors on manipulator hand. Prototype is early, subsystem-level product of continuing effort to develop automated system that assists in training and supervising human control operator: provides symbolic feedback (e.g., warnings of impending collisions or evaluations of performance) to operator in real time during successive executions of same task. Also simplifies transition between teleoperation and autonomous modes of telerobotic system.
Data on forces and torques measured in experiments with remote manipulators processed into spectral signatures via special frequency-analysis procedure. Spectral signatures complement other measures used to evaluate performances of telerobotic systems and human operators. Contributes to verification of some assumptions made in designing manipulator arms and control subsystems and used as feedback by operators engaged in realtime monitoring of telerobotic tasks. Also provides useful indications of flows of power between manipulators and their environments.
Laboratory telerobotic system performs such complicated tasks as picking up tools, removing thermal blanket, and replacing screws. Human operator in control room operates remote robot with aid of video monitors, torque and force displays, and force feedback. System used to perform research and to develop telerobotic-repair capabilities equal to those of human operator.
Teleoperation experiments at JPL have shown that advanced features in a telerobotic system are a necessary condition for good results, but that they are not sufficient to assure consistently good performance by the operators. Two or three operators are normally used during training and experiments to maintain the desired performance. An alternative to this multi-operator control station is a man-machine interface embedding computer programs that can perform some of the operator's functions. In this paper we present our first experiments with these concepts, in which we focused on the areas of real-time task monitoring and interactive path planning. In the first case, when performing a known task, the operator has an automatic aid for setting control parameters and camera views. In the second case, an interactive path planner will rank different path alternatives so that the operator will make the correct control decision. The monitoring function has been implemented with a neural network doing the real-time task segmentation. The interactive path planner was implemented for redundant manipulators to specify arm configurations across the desired path and satisfy geometric, task, and performance constraints.
Boolean neural networks proposed to implement part of intermediate level of hierarchical architecture of control system for artificially intelligent control of robot hand. Concept described in "Architecture for Intelligent Control of Robotic Tasks" (NPO-17871). Rule level of architecture implemented in two Boolean neural networks operated and updated in alternation. No explicit programming of network. Internal configuration not unique but, depends on initial state and history of previous adaptations. Accepts new rules sequentially presented by external controller.
In the last few years, teleoperated tasks have been the subject of extensive research to determine the best combination of control modalities according to specific criteria. The operator's performance were compared on the basis of task completion time and of force and torque measurements during the tasks. This paper proposes a procedure for the spectral analysis of force and torque signals generated during teleoperation experiments. There are two main reasons for examining teleoperation data in the frequency domain: a spectral analysis of different tasks can validate the assumptions made in the design of the teleoperator, and a task's frequency signature can be a valuable measure of the operator's performance.
Telerobotics/EVA Joint Analysis Systems (TEJAS) computer program is hypermedia information software system using object-oriented programming to bridge gap between crew-EVA and telerobotics activities. TEJAS Version 1.0 contains 20 HyperCard stacks using visual, customizable interface of icon buttons, pop-up menus, and relational commands to store, link, and standardize related information about primitives, technologies, tasks, assumptions, and open issues involved in space-telerobot or crew-EVA tasks. Runs on any Apple MacIntosh personal computer.
Proposed architecture for control of such robotic devices as artificial hands calls for data-abstracting hierarchies of processing, controlling, and sensing equipment that plans, executes, and corrects movements of devices at acceptably high rates. Combines features developed in research on artificial intelligence and control theory. Characterized by casual connections between layers of hierarchy, approximately equal complexities of layers, and directed focus of attention.
An architecture is proposed for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of boolean rules and general planning operations. Layers implementation has to be consistent with the type of operation and its requirements for real time control. It is proposed to implement the rule level with a Boolean Artificial Neural Network characterized by a response time sufficient for producing reflex corrective action at the actuator level.
By means of a system of parallel coordinates, a nonprojective mapping from R exp N to R squared is obtained for any positive integer N. In this way multivariate data and relations can be represented in the Euclidean plane (embedded in the projective plane). Basically, R squared with Cartesian coordinates is augmented by N parallel axes, one for each variable. The N joint variables of a robotic device can be represented graphically by using parallel coordinates. It is pointed out that some properties of the relation are better perceived visually from the parallel coordinate representation, and that new algorithms and data structures can be obtained from this representation. The main features of parallel coordinates are described, and an example is presented of their use for configuration space representation of a mechanical arm (where Cartesian coordinates cannot be used).
This paper describes an architecture for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of Boolean rules and general planning operations. The implementation of the layer has to be consistent with the type of operation and its requirements for real time control. One implementation of the rule level, with a Boolean artificial neural network which would have a response time sufficient for producing reflex corrective action at the actuator level is presented.