Estimation and inference for grasping and manipulation tasks using vision and kinesthetic sensors

This thesis presents a novel framework for state estimation in the context of robotic grasping and manipulation. The overall estimation approach is based on fusing various visual cues for manipulator tracking, namely appearance and feature-based, shape-based, and silhouette-based visual cues. Similarly, a framework is developed to fuse the above visual cues, but also kinesthetic cues such as force-torque and tactile measurements, for in-hand object pose estimation. The cues are extracted from multiple sensor modalities and are fused in a variety of Kalman filters.

A hybrid estimator is developed to estimate both a continuous state (robot and object states) and discrete states, called contact modes, which specify how each finger contacts a particular object surface. A static multiple model estimator is used to compute and maintain this mode probability. The thesis also develops an estimation framework for estimating model parameters associated with object grasping. Dual and joint state-parameter estimation is explored for parameter estimation of a grasped object's mass and center of mass. Experimental results demonstrate simultaneous object localization and center of mass estimation.

Dual-arm estimation is developed for two arm robotic manipulation tasks. Two types of filters are explored; the first is an augmented filter that contains both arms in the state vector while the second runs two filters in parallel, one for each arm. These two frameworks and their performance is compared in a dual-arm task of removing a wheel from a hub.

This thesis also presents a new method for action selection involving touch. This next best touch method selects an available action for interacting with an object that will gain the most information. The algorithm employs information theory to compute an information gain metric that is based on a probabilistic belief suitable for the task. An estimation framework is used to maintain this belief over time. Kinesthetic measurements such as contact and tactile measurements are used to update the state belief after every interactive action. Simulation and experimental results are demonstrated using next best touch for object localization, specifically a door handle on a door. The next best touch theory is extended for model parameter determination. Since many objects within a particular object category share the same rough shape, principle component analysis may be used to parametrize the object mesh models. These parameters can be estimated using the action selection technique that selects the touching action which best both localizes and estimates these parameters. Simulation results are then presented involving localizing and determining a parameter of a screwdriver.

Lastly, the next best touch theory is further extended to model classes. Instead of estimating parameters, object class determination is incorporated into the information gain metric calculation. The best touching action is selected in order to best discern between the possible model classes. Simulation results are presented to validate the theory.

Iso-specific Ziegler-Natta polymerization of α-olefins with a single-component organoyttrium catalyst

The synthesis of a sterically tailored ligand array (M)_2((C_5H_2-2-Si(CH_3)_3-4-C(CH_3)_3)S_2i(CH_3)_2]("M_2Bp") (M = Li, 16; K, 19) is described. Transmetallation of Li_2Bp with YCl_3(THF)_3 affords exclusively the C_2 symmetric product rac-[BpY(µ_2-Cl)_2Li(THF)_2], 20. A X-ray crystal structure of 20 has been determined; triclinic, P1, a= 13.110 (8), b = 17.163 (15), c = 20.623 (14) Å, α = 104.02 (7), β = 99.38 (5), γ = 100.24 (6)° , Z = 4, R = 0.056. Transmetallation of K_2Bp with YCl_3(THF)_3 affords the halide free complex rac-BpYCl, 23. The corresponding rac-BpLaCl, 28, is prepared in an anlogous manner. In all cases the achiral meso isomer is not obtained since only for the racemic isomers are the unfavorable steric interactions between the Si(CH3)_3 groups in the narrow portion of the [Cp-M'-Cp] wedge avoided. Alkylation of 20 or 23 with LiCH(Si(CH_3)_3)_2 affords rac-BpYCH(Si(CH_3)_3)_2, 26 in good yield. Alkylation of 28 with LiCH(Si(CH_3)_3)_2 affords rac-BpLaCH(Si(CH_3)_3)_2 29. Hydrogenation of 26 cleanly affords the bridging hydride species [BpY(µ_2-H)]_2, 27, as the homochiral (R,R) and (S,S) dimeric pairs. 26 is an efficient initiator for the polymerization of ethylene to high molecular weight linear polyethylene. 27 catalyzes the polymerization of propylene (25% v/v in methylcyclohexane) and neat samples of 1-butene, 1-pentene, 1-hexene to moderately high molecular weight polymers: polypropylene (M_n = 4,200, PDI 2.32, T_m 157 °C); poly-1-butene (M_n = 8,500, PDI 3.44, T_m 105 °C); poly-1-pentene (M_n = 20,000, PDI 1.99, T_m 73 °C); poly-1-hexene (M_n = 24,000, PDI 1.75, T_m < 25 °C). ^(13)C NMR spectra at the pentad analysis level indicates that the degree of isotacticity is 99% mmmm for all polymer samples. 27 is the first single component iso-specific α-olefin polymerization catalyst. The presumed origins of the high isospecificity are presented.

Coupled effects of mechanics, geometry, and chemistry on bio-membrane behavior

Lipid bilayer membranes are models for cell membranes--the structure that helps regulate cell function. Cell membranes are heterogeneous, and the coupling between composition and shape gives rise to complex behaviors that are important to regulation. This thesis seeks to systematically build and analyze complete models to understand the behavior of multi-component membranes.

We propose a model and use it to derive the equilibrium and stability conditions for a general class of closed multi-component biological membranes. Our analysis shows that the critical modes of these membranes have high frequencies, unlike single-component vesicles, and their stability depends on system size, unlike in systems undergoing spinodal decomposition in flat space. An important implication is that small perturbations may nucleate localized but very large deformations. We compare these results with experimental observations.

We also study open membranes to gain insight into long tubular membranes that arise for example in nerve cells. We derive a complete system of equations for open membranes by using the principle of virtual work. Our linear stability analysis predicts that the tubular membranes tend to have coiling shapes if the tension is small, cylindrical shapes if the tension is moderate, and beading shapes if the tension is large. This is consistent with experimental observations reported in the literature in nerve fibers. Further, we provide numerical solutions to the fully nonlinear equilibrium equations in some problems, and show that the observed mode shapes are consistent with those suggested by linear stability. Our work also proves that beadings of nerve fibers can appear purely as a mechanical response of the membrane.

Macroscopically Dissipative Systems with Underlying Microscopic Dynamics : Properties and Limits of Measurement

While some of the deepest results in nature are those that give explicit bounds between important physical quantities, some of the most intriguing and celebrated of such bounds come from fields where there is still a great deal of disagreement and confusion regarding even the most fundamental aspects of the theories. For example, in quantum mechanics, there is still no complete consensus as to whether the limitations associated with Heisenberg's Uncertainty Principle derive from an inherent randomness in physics, or rather from limitations in the measurement process itself, resulting from phenomena like back action. Likewise, the second law of thermodynamics makes a statement regarding the increase in entropy of closed systems, yet the theory itself has neither a universally-accepted definition of equilibrium, nor an adequate explanation of how a system with underlying microscopically Hamiltonian dynamics (reversible) settles into a fixed distribution.

Motivated by these physical theories, and perhaps their inconsistencies, in this thesis we use dynamical systems theory to investigate how the very simplest of systems, even with no physical constraints, are characterized by bounds that give limits to the ability to make measurements on them. Using an existing interpretation, we start by examining how dissipative systems can be viewed as high-dimensional lossless systems, and how taking this view necessarily implies the existence of a noise process that results from the uncertainty in the initial system state. This fluctuation-dissipation result plays a central role in a measurement model that we examine, in particular describing how noise is inevitably injected into a system during a measurement, noise that can be viewed as originating either from the randomness of the many degrees of freedom of the measurement device, or of the environment. This noise constitutes one component of measurement back action, and ultimately imposes limits on measurement uncertainty. Depending on the assumptions we make about active devices, and their limitations, this back action can be offset to varying degrees via control. It turns out that using active devices to reduce measurement back action leads to estimation problems that have non-zero uncertainty lower bounds, the most interesting of which arise when the observed system is lossless. One such lower bound, a main contribution of this work, can be viewed as a classical version of a Heisenberg uncertainty relation between the system's position and momentum. We finally also revisit the murky question of how macroscopic dissipation appears from lossless dynamics, and propose alternative approaches for framing the question using existing systematic methods of model reduction.