From First Contact to Close Encounters: A Developmentally Deep Perceptual System for a Humanoid Robot

This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply 'pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively. The motivation for this work is simple. Training on large corpora of annotated real-world data has proven crucial for creating robust solutions to perceptual problems such as speech recognition and face detection. But the powerful tools used during training of such systems are typically stripped away at deployment. Ideally they should remain, particularly for unstable tasks such as object detection, where the set of objects needed in a task tomorrow might be different from the set of objects needed today. The key limiting factor is access to training data, but as this thesis shows, that need not be a problem on a robotic platform that can actively probe its environment, and carry out experiments to resolve ambiguity. This work is an instance of a general approach to learning a new perceptual judgment: find special situations in which the perceptual judgment is easy and study these situations to find correlated features that can be observed more generally.

Model Selection in Summary Evaluation

A difficulty in the design of automated text summarization algorithms is in the objective evaluation. Viewing summarization as a tradeoff between length and information content, we introduce a technique based on a hierarchy of classifiers to rank, through model selection, different summarization methods. This summary evaluation technique allows for broader comparison of summarization methods than the traditional techniques of summary evaluation. We present an empirical study of two simple, albeit widely used, summarization methods that shows the different usages of this automated task-based evaluation system and confirms the results obtained with human-based evaluation methods over smaller corpora.

Synthesis and Aggregation Behavior of Pluronic F87/Poly(acrylic acid) Block Copolymer with Doxorubicin

Poly(acrylic acid) (PAA) was grafted onto both termini of Pluronic F87 (PEO₆₇-PPO₃₉-PEO₆₇) via atom transfer radical polymerization to produce a novel muco-adhesive block copolymer PAA₈₀-b-F₈₇-b-PAA₈₀. It was observed that PAA₈₀-F₈₇-PAA₈₀ forms stable complexes with weakly basic anti-cancer drug, Doxorubicin. Thermodynamic changes due to the drug binding to the copolymer were assessed at different pH by isothermal titration calorimetry (ITC). The formation of the polymer/drug complexes was studied by turbidimetric titration and dynamic light scattering. Doxorubicin and PAA-b-F87-b-PAA block copolymer are found to interact strongly in aqueous solution via non-covalent interactions over a wide pH range. At pH>4.35, drug binding is due to electrostatic interactions. Hydrogen-bond also plays a role in the stabilization of the PAA₈₀-F₈₇-PAA₈₀/DOX complex. At pH 7.4 (α=0.8), the size and stability of polymer/drug complex depend strongly on the doxorubicin concentration. When CDOX <0.13mM, the PAA₈₀-F₈₇-PAA₈₀ copolymer forms stable inter-chain complexes with DOX (110 ~ 150 nm). When CDOX >0.13mM, as suggested by the light scattering result, the reorganization of the polymer/drug complex is believed to occur. With further addition of DOX (CDOX >0.34mM), sharp increase in the turbidity indicates the formation of large aggregates, followed by phase separation. The onset of a sharp enthalpy increase corresponds to the formation of a stoichiometric complex.