An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Adaptive pattern recognition based control system and method

A mobile communications device comprising a location sensing system, producing a location output; a memory, storing a set of locations and associated events; a telecommunications device, communicating event and location information between a remote system and said memory; and a processor, processing said location output in conjunction with said stored locations and associated events in said memory, to determine a priority thereof.

Mobile communication device

The principal components and capabilities of Blanche, an autonomous robot vehicle, are described. Blanche is designed for use in structured office or factory environments rather than unstructured natural environments, and it is assumed that an offline path planner provides the vehicle with a series of collision-free maneuvers, consisting of line and arc segments, to move the vehicle to a desired position. These segments are sent to a low-level trajectory generator and closed-loop motion control. The controller assumes accurate knowledge of the vehicle's position. Blanche's position estimation system consists of a priori map of its environment and a robust matching algorithm. The matching algorithm also estimates the precision of the corresponding match/correction that is then optimally (in a maximum-likelihood sense) combined with the current odometric position to provide an improved estimate of the vehicle's position. The system does not use passive or active beacons. Experimental results are reported. >

Blanche-an experiment in guidance and navigation of an autonomous robot vehicle

We formulate the kinematic equations of motion of wheeled mobile robots incorporating conventional, omnidirectional, and ball wheels.1 We extend the kinematic modeling of stationary manipulators to accommodate such special characteristics of wheeled mobile robots as multiple closed-link chains, higher-pair contact points between a wheel and a surface, and unactuated and unsensed wheel degrees of freedom. We apply the Sheth-Uicker convention to assign coordinate axes and develop a matrix coordinate transformation algebra to derive the equations of motion. We introduce a wheel Jacobian matrix to relate the motions of each wheel to the motions of the robot. We then combine the individual wheel equations to obtain the composite robot equation of motion. We interpret the properties of the composite robot equation to characterize the mobility of a wheeled mobile robot according to a mobility characterization tree. Similarly, we apply actuation and sensing characterization trees to delineate the robot motions producible by the wheel actuators and discernible by the wheel sensors, respectively. We calculate the sensed forward and actuated inverse solutions and interpret the physical conditions which guarantee their existence. To illustrate the development, we formulate and interpret the kinematic equations of motion of Uranus, a wheeled mobile robot being constructed in the CMU Mobile Robot Laboratory.

Kinematic modeling of wheeled mobile robots

Systems and methods allow for the accurate determination of the terrestrial position of an autonomous vehicle in real time. A first position estimate of the vehicle 102 is derived from satellites of a global positioning system and/or a pseudolite(s). The pseudolite(s) may be used exclusively when the satellites are not in the view of the vehicle. A second position estimate is derived from an inertial reference unit and/or a vehicle odometer. The first and second position estimates are combined and filtered using novel techniques to derive a more accurate third position estimate of the vehicle's position. Accordingly, accurate autonomous navigation of the vehicle can be effectuated using the third position estimate.

Vehicle position determination system and method

An obstacle data processing system for an unmanned self-controlled vehicle, capable of enabling the vehicle to automatically avert any obstacle which lies in the course of running of the vehicle. The system has obstacle position memory device capable of accumulating position data concerning specific obstacles and, hence, forming data concerning the distribution of the obstacles. The vehicle therefore can conduct appropriate averting operation in accordance with the distribution of a plurality of obstacles.

Obstacle data processing system for unmanned vehicle

An automatically guided vehicle, traveling without fixed guide ways, has been developed In this paper, the construction of the vehicle, the control algorithm, and its general performance are described

An automatic guidance system of a self-controlled vehicle

An automatically guided vehicle, traveling without fixed guide ways, has been developed. In this paper, the construction of the vehicle, the control algorithm, and its general performance are described.

An Automatic Guidance System of a Self-Controlled Vehicle

A fluctuating drive system comprises: random generating means for generating a randomly varying physical quantity; control means for controlling the randomly varying physical quantity; amplifying means for amplifying the controlled physical quantity; and driving means for driving an energy generating means in accordance with the amplified physical quantity, thereby to generate the randomly varying energy from the energy generating means. With this system, the environment or stimulus is positively fluctuated at random with l/f characteristics or the like.

Fluctuating drive system

An automatic guidance system for an unmanned vehicle causes the unmanned vehicle to move to a destination by a combination of traveling along a preset course, and turning and stopping at predetermined positions. A running control unit is provided to determine optimal control values in such a manner that a running state of the unmanned vehicle after a predetermined period of time is predicted by changing control values set in a drive unit in accordance with state values (e.g., position information and heading angle information) representing the current running state, and that the running state after the predetermined period of time matches with the directed operation of the unmanned vehicle, thereby accurately guiding the unmanned vehicle along the preset path.

Hideo Arakawa

Papers

Obstacle data processing system for unmanned vehicle

An automatic guidance system of a self-controlled vehicle

An Automatic Guidance System of a Self-Controlled Vehicle

Fluctuating drive system

Automatic guidance system for an unmanned vehicle