Contact Sensing: A Sequential Decision Approach to Sensing Manipulation Contact

This paper describes a new statistical, model-based approach to building a contact state observer. The observer uses measurements of the contact force and position, and prior information about the task encoded in a graph, to determine the current location of the robot in the task configuration space. Each node represents what the measurements will look like in a small region of configuration space by storing a predictive, statistical, measurement model. This approach assumes that the measurements are statistically block independent conditioned on knowledge of the model, which is a fairly good model of the actual process. Arcs in the graph represent possible transitions between models. Beam Viterbi search is used to match measurement history against possible paths through the model graph in order to estimate the most likely path for the robot. The resulting approach provides a new decision process that can be use as an observer for event driven manipulation programming. The decision procedure is significantly more robust than simple threshold decisions because the measurement history is used to make decisions. The approach can be used to enhance the capabilities of autonomous assembly machines and in quality control applications.

Pose Determination of a Grasped Object Using Limited Sensing

This report explores methods for determining the pose of a grasped object using only limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust.

Effect of Gas Sparging in Mammalian Cell Bioreactors

One of the major problems in the operations of mammalian cell bioreactors is the detrimental effect of gas sparging. Since the most convenient way to oxygenate any bioreactor is by gas sparging, this adverse effect has often been one of the limiting oxygen transport problems in both laboratory and industrial mammalian cell bioreactors. When one examines the literature on the effect of gas sparging on the death of mammalian cells, a great deal of confusions has been reported. It is not clear from the published literature as to the leading cause for gas-sparged related cell death. These confusions prevent the rational design and operations of mammalian cell bioreactors. In our laboratory, we have attempted to address this problem both fundamentally as well as attempt to obtain a general understanding on the adverse effect of gas sparging. Our analyses first examined the fluid shear associated with the various sections that the gas bubbles encounter during entrance, passage through the bioreactor and the final exit of the gas bubbles. Our analyses showed that the major damage of the mammalian cells by gas bubbles is due to the burst of the bubbles when exiting the bioreactor. It was also our hypothesis that the entrained cells in the liquid boundary layer of the gas bubble upon bursting is the major cause for cell death. We have corroborated this hypothesis by correlating the liquid entrainment with the cell death rate using results from our laboratory as well as other studies. Pluonic F-68, a weak surfactant, has routinely been used in laboratory and industrial bioreactors. In the past, the protective effect of Pluronic F-68 has never been shown as to why it is effective. In our research, we have data using microphotography which clearly demonstrated and corroborated our entrainment hypothesis is the major reason for the effectiveness of Pluronic F-68 in protecting the cells from gas-sparged related cell death.