Torts—Fair Comment

Julian v. American Business Consultants, Inc ., 2 N. Y. 2d 1, 137 N. E. 2d 1 (1956)

Torts—Hospital Immunity from Tort Liability

Berg v. N. Y. Society for the Relief of the Ruptured and Crippled, 1 N. Y. 2d 499, 136 N. E. 2d 523 (1956)

Torts—Defamation Per Se

Nichols v. Item Publishers, Inc., 309 N. Y. 596, 132 N.E. 2d 860 (1956)

Torts—False Arrest

Squadrito v. Griebsch, 1 N. Y. 2d. 471, 136 N. E. 2d. 504 (1956)

Torts—Testamentary Libel

Brown v. Dufrey, 1 N. Y. 2d 190, 134 N. E. 2d 469 (1956)

Torts—Hospital Immunity from Tort Liability

Berg v. N. Y. Society for the Relief of the Ruptured and Crippled, 1 N. Y. 2d 499, 136 N. E. 2d 523 (1956)

Evidence—Affidavit Concerning Jurors’ Unauthorized View Inadmissible as Ground for New Trial

People v. DeLucia, 15 N.Y.2d 294, 206 N.E.2d 324, 258 N.Y.S.2d 377 (1965), cert. denied, 34 U.S.L. Week 3106 (U.S. Oct. 12, 1965)

Laser transit anemometer and Pitot probe comparative measurements in a sharp cone boundary layer at Mach 4

Laser transit anemometer (LTA) measurements of a 7 degree sharp cone boundary layer were conducted in the Air Force/AEDC Supersonic Tunnel A Mach 4 flow field. These measurements are compared with Pitot probe measurements and tricone theory provided by AEDC staff. Measurements were made both in laminar and turbulent boundary layers of the model. Comparison of LTA measurements with theory showed agreement to better than 1 percent for the laminar boundary layer cases. This level of agreement was obtained after small position corrections, 0.01 to 0.6 mm, were applied to the experimental data sets. Pitot probe data when compared with theory also showed small positioning errors. The Pitot data value was also limited due to probe interference with the flow near the model. The LTA turbulent boundary layer data indicated a power law dependence of 6.3 to 6.9. The LTA data was analyzed in the time (Tau) domain in which it was obtained and in the velocity domain. No significant differences were noted between Tau and velocity domain results except in one turbulent boundary layer case

A hypothesis-based algorithm for planning and control in non-Gaussian belief spaces

We consider the partially observable control problem where it is potentially necessary to perform complex information-gathering operations in order to localize state. One approach to solving these problems is to create plans in belief-space, the space of probability distributions over the underlying state of the system. The belief-space plan encodes a strategy for performing a task while gaining information as necessary. Most approaches to belief-space planning rely upon representing belief state in a particular way (typically as a Gaussian). Unfortunately, this can lead to large errors between the assumed density representation and the true belief state. We propose a new computationally efficient algorithm for planning in non-Gaussian belief spaces. We propose a receding horizon re-planning approach where planning occurs in a low-dimensional sampled representation of belief state while the true belief state of the system is monitored using an arbitrary accurate high-dimensional representation. Our key contribution is a planning problem that, when solved optimally on each re-planning step, is guaranteed, under certain conditions, to enable the system to gain information. We prove that when these conditions are met, the algorithm converges with probability one. We characterize algorithm performance for different parameter settings in simulation and report results from a robot experiment that illustrates the application of the algorithm to robot grasping