The paper involves the development of real-time estimation and control details for a new vision-based manipulator con trol method. The method permits a kind of adaptability not otherwise available in that the relationship between the cam era-space location of manipulable visual cues and the vector of manipulator joint coordinates is estimated in real time. This is done based upon a model that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation as well as uncertainty of manipulator grasp. Both large-scale trajectory planning and refined placement precision become possible despite an un known camera-manipulator juxtaposition. This feature opens the door to a range of applications of manipulation, includ ing a mobile manipulator with stationary cameras tracking and providing information for control of the manipulation event. Evidence of the ability of the estimation algorithm to perform in real time is provided with a successfully performed interception task, completed without a priori knowledge of camera or manipulator positions.

This article extends to three-dimensional tasks the method of camera space manipulation. A minimum of two cameras is required to place points on end effectors (or objects in their grasp) of n-degree-of-freedom manipulators relative to other bodies. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. A precise and robust manipulation strategy that is compatible with "real time" results. Simulations are used that show the method to be insensitive to two particular kinds of model error- unmodeled elastic deflection and unmodeled camera distortion. The method is tested experimentally with a three- dimensional point placement task. It is then generalized to rigid body placement tasks and illustrated with experiments involving the positioning of one rigid body on a second. An appendix details the unfolding of one such experimental maneuver at several junctures in the visual data-collecting process.

Generalized EEG seizures were induced in acute, conscious New Zealand albino rabbits with intravenous pentylenetetrazol (PTZ) (10 or 15 mg/kg) or electrical stimulation of the frontal cerebral cortex (ELEC) (50 Hz, 1 msec pulse duration, 2 sec train duration, 4.0-7.6 V). Three anticonvulsant treatments were compared: (1) electrical transhemispheral stimulation of the ansiform or simplex cerebellar lobes (10 Hz, 1.5 msec, 3-4 V), (2) phenobarbital (PB) (25 mg/kg, i.v.), and (3) diphenylhydantoin (DPH) (30 mg/kg, i.v.). After treatment, increments in PTZ dose or stimulation voltage were applied until a seizure was evoked that approximated the original in severity and duration. PTZ seizure thresholds were not elevated by DPH, and electrically induced seizure thresholds were not elevated by cerebellar stimulation (CBL). The four remaining seizure threshold elevations (increase in PTZ dose or stimulation voltage) were significant at a level of 0.025 or greater. Comparison of the elevations of seizure thresholds showed no differences at the 0.01 level of significance. Thus, no differences were seen between elevation of PTZ seizure thresholds by CBL or PB, or elevation of electrically induced seizure thresholds by PB or DPH, when examined on an acute basis.

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The paper extends to wheeled systems the method of camera-space manipulation. A minimum of two cameras is required to place points on end-effectors (or objects in their grasp) of n-degree-of-freedom manipulators relative to other bodies where the nonholonomic degrees of freedom on a mobile manipulator base may be included. The target bodies do not have a precisely known location relative to the environment. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras, resulting in a precise and robust manipulation strategy that is compatible with "real time." The method is illustrated experimentally, though not in real time, using a point placement task. It is then generalized to rigid-body positioning tasks. Although the experimental point placement illustrations make use of a very simple trajectory planning scheme for the wheels of the base, a smoother optimal trajectory planning scheme that makes use of the Pontryagin maximum principle is also developed and illustrated. In a departure from the normal practice of using time as the independent variable for estimation and optimal trajectory planning algorithms, the present development is time independent and instead introduces the forward rotation of the drive wheel of the base as the independent variable.