Sample-based motion planning in high-dimensional and differentially-constrained systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 115-124).State of the art sample-based path planning algorithms, such as the Rapidly-exploring Random Tree (RRT), have proven to be effective in path planning for systems subject to complex kinematic and geometric constraints. The performance of these algorithms, however, degrade as the dimension of the system increases. Furthermore, sample-based planners rely on distance metrics which do not work well when the system has differential constraints. Such constraints are particularly challenging in systems with non-holonomic and underactuated dynamics. This thesis develops two intelligent sampling strategies to help guide the search process. To reduce sensitivity to dimension, sampling can be done in a low-dimensional task space rather than in the high-dimensional state space. Altering the sampling strategy in this way creates a Voronoi Bias in task space, which helps to guide the search, while the RRT continues to verify trajectory feasibility in the full state space. Fast path planning is demonstrated using this approach on a 1500-link manipulator. To enable task-space biasing for underactuated systems, a hierarchical task space controller is developed by utilizing partial feedback linearization. Another sampling strategy is also presented, where the local reachability of the tree is approximated, and used to bias the search, for systems subject to differential constraints. Reachability guidance is shown to improve search performance of the RRT by an order of magnitude when planning on a pendulum and non-holonomic car. The ideas of task-space biasing and reachability guidance are then combined for demonstration of a motion planning algorithm implemented on LittleDog, a quadruped robot. The motion planning algorithm successfully planned bounding trajectories over extremely rough terrain.by Alexander C. Shkolnik.Ph.D

Asymptotically-optimal path planning for manipulation using incremental sampling-based algorithms

A desirable property of path planning for robotic manipulation is the ability to identify solutions in a sufficiently short amount of time to be usable. This is particularly challenging for the manipulation problem due to the need to plan over high-dimensional configuration spaces and to perform computationally expensive collision checking procedures. Consequently, existing planners take steps to achieve desired solution times at the cost of low quality solutions. This paper presents a planning algorithm that overcomes these difficulties by augmenting the asymptotically-optimal RRT* with a sparse sampling procedure. With the addition of a collision checking procedure that leverages memoization, this approach has the benefit that it quickly identifies low-cost feasible trajectories and takes advantage of subsequent computation time to refine the solution towards an optimal one. We evaluate the algorithm through a series of Monte Carlo simulations of seven, twelve, and fourteen degree of freedom manipulation planning problems in a realistic simulation environment. The results indicate that the proposed approach provides significant improvements in the quality of both the initial solution and the final path, while incurring almost no computational overhead compared to the RRT algorithm. We conclude with a demonstration of our algorithm for single-arm and dual-arm planning on Willow Garage's PR2 robot

Fluid-structure interaction in abdominal aortic aneurysms: effects of asymmetry and wall thickness

BACKGROUND: Abdominal aortic aneurysm (AAA) is a prevalent disease which is of significant concern because of the morbidity associated with the continuing expansion of the abdominal aorta and its ultimate rupture. The transient interaction between blood flow and the wall contributes to wall stress which, if it exceeds the failure strength of the dilated arterial wall, will lead to aneurysm rupture. Utilizing a computational approach, the biomechanical environment of virtual AAAs can be evaluated to study the affects of asymmetry and wall thickness on this stress, two parameters that contribute to increased risk of aneurysm rupture. METHODS: Ten virtual aneurysm models were created with five different asymmetry parameters ranging from β = 0.2 to 1.0 and either a uniform or variable wall thickness to study the flow and wall dynamics by means of fully coupled fluid-structure interaction (FSI) analyses. The AAA wall was designed to have a (i) uniform 1.5 mm thickness or (ii) variable thickness ranging from 0.5 – 1.5 mm extruded normally from the boundary surface of the lumen. These models were meshed with linear hexahedral elements, imported into a commercial finite element code and analyzed under transient flow conditions. The method proposed was then compared with traditional computational solid stress techniques on the basis of peak wall stress predictions and cost of computational effort. RESULTS: The results provide quantitative predictions of flow patterns and wall mechanics as well as the effects of aneurysm asymmetry and wall thickness heterogeneity on the estimation of peak wall stress. These parameters affect the magnitude and distribution of Von Mises stresses; varying wall thickness increases the maximum Von Mises stress by 4 times its uniform thickness counterpart. A pre-peak systole retrograde flow was observed in the AAA sac for all models, which is due to the elastic energy stored in the compliant arterial wall and the expansion force of the artery during systole. CONCLUSION: Both wall thickness and geometry asymmetry affect the stress exhibited by a virtual AAA. Our results suggest that an asymmetric AAA with regional variations in wall thickness would be exposed to higher mechanical stresses and an increased risk of rupture than a more fusiform AAA with uniform wall thickness. Therefore, it is important to accurately reproduce vessel geometry and wall thickness in computational predictions of AAA biomechanics

Molecular Characterization of a Strawberry FaASR Gene in Relation to Fruit Ripening

BACKGROUND: ABA-, stress- and ripening-induced (ASR) proteins have been reported to act as a downstream component involved in ABA signal transduction. Although much attention has been paid to the roles of ASR in plant development and stress responses, the mechanisms by which ABA regulate fruit ripening at the molecular level are not fully understood. In the present work, a strawberry ASR gene was isolated and characterized (FaASR), and a polyclonal antibody against FaASR protein was prepared. Furthermore, the effects of ABA, applied to two different developmental stages of strawberry, on fruit ripening and the expression of FaASR at transcriptional and translational levels were investigated. METHODOLOGY/PRINCIPAL FINDINGS: FaASR, localized in the cytoplasm and nucleus, contained 193 amino acids and shared common features with other plant ASRs. It also functioned as a transcriptional activator in yeast with trans-activation activity in the N-terminus. During strawberry fruit development, endogenous ABA content, levels of FaASR mRNA and protein increased significantly at the initiation of ripening at a white (W) fruit developmental stage. More importantly, application of exogenous ABA to large green (LG) fruit and W fruit markedly increased endogenous ABA content, accelerated fruit ripening, and greatly enhanced the expression of FaASR transcripts and the accumulation of FaASR protein simultaneously. CONCLUSIONS: These results indicate that FaASR may be involved in strawberry fruit ripening. The observed increase in endogenous ABA content, and enhanced FaASR expression at transcriptional and translational levels in response to ABA treatment might partially contribute to the acceleration of strawberry fruit ripening

Estimating the Ultraviolet Emission of M dwarfs with Exoplanets from Ca II and Hα\alpha

M dwarf stars are excellent candidates around which to search for exoplanets, including temperate, Earth-sized planets. To evaluate the photochemistry of the planetary atmosphere, it is essential to characterize the UV spectral energy distribution of the planet's host star. This wavelength regime is important because molecules in the planetary atmosphere such as oxygen and ozone have highly wavelength dependent absorption cross sections that peak in the UV (900-3200 $\r{A}$). We seek to provide a broadly applicable method of estimating the UV emission of an M dwarf, without direct UV data, by identifying a relationship between non-contemporaneous optical and UV observations. Our work uses the largest sample of M dwarf star far- and near-UV observations yet assembled. We evaluate three commonly-observed optical chromospheric activity indices -- H$\alpha$ equivalent widths and log$_{10}$ L$_{H\alpha}$/L$_{bol}$, and the Mount Wilson Ca II H&K S and R$'_{HK}$ indices -- using optical spectra from the HARPS, UVES, and HIRES archives and new HIRES spectra. Archival and new Hubble Space Telescope COS and STIS spectra are used to measure line fluxes for the brightest chromospheric and transition region emission lines between 1200-2800 $\r{A}$. Our results show a correlation between UV emission line luminosity normalized to the stellar bolometric luminosity and Ca II R$'_{HK}$ with standard deviations of 0.31-0.61 dex (factors of $\sim$2-4) about the best-fit lines. We also find correlations between normalized UV line luminosity and H$\alpha$ log$_{10}$ L$_{H\alpha}$/L$_{bol}$ and the S index. These relationships allow one to estimate the average UV emission from M0 to M9 dwarfs when UV data are not available.Comment: 34 pages, 12 figures, 5 tables (one machine readable table available online). Accepted to AAS Journal

and a Framework for Studying Learning in Vitro By

In presenting this thesis as a partial fulfillment of the requirements for an advanced degree from Emory University, I agree that the Library of the University shall make it available for inspection and circulation in accordance with its regulations governing materials of this type. I agree that permission to copy from, or to publish, this thesis may be granted by the professor under whose direction it was prepared, or, in his absence, by the Dean of the Graduate School when such copying or publication is solely for scholarly purposes and does not involve potential financial gain. It is understood that any copying from, or publication of, this thesis that involves potential financial gain will not be allowed without written permission. ________________________________

ICEF2005-1221 HIGH EFFICIENCY HYBRID CYCLE ENGINE

ABSTRACT A "High Efficiency Hybrid Cycle" (HEHC) thermodynamic cycle is explored. This four-stroke cycle borrows elements from Otto, Diesel, Atkinson, and Rankine cycles. Air is compressed into an isolated combustion chamber, allowing for true isochoric combustion, and extended duration for combustion to proceed until completion. Combustion products expand into a chamber with greater volume than intake. We provide details of a compact HEHC design implementation using rotary pistons and isolated rotating combustion chambers. Two Pistons simultaneously rotate and reciprocate and are held in position by two roller bearings. One Piston performs intake and compression, while the other performs exhaust and expansion. We predict a reduction of energy losses, moving part counts, weight and size over conventional engines

Path planning in 1000+ dimensions using a task-space Voronoi bias

The reduction of the kinematics and/or dynamics of a high-DOF robotic manipulator to a low-dimension ldquotask spacerdquo has proven to be an invaluable tool for designing feedback controllers. When obstacles or other kinodynamic constraints complicate the feedback design process, motion planning techniques can often still find feasible paths, but these techniques are typically implemented in the high-dimensional configuration (or state) space. Here we argue that providing a Voronoi bias in the task space can dramatically improve the performance of randomized motion planners, while still avoiding non-trivial constraints in the configuration (or state) space. We demonstrate the potential of task-space search by planning collision-free trajectories for a 1500 link arm through obstacles to reach a desired end-effector position.United States. Defense Advanced Research Projects Agency (Learning Locomotion program (AFRL contract # FA8650-05-C-7262)

Reachability-guided sampling for planning under differential constraints

Rapidly-exploring random trees (RRTs) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency of these algorithms can be severely compromised in the presence of certain kinodynamics constraints. Obstacle fields with tunnels, or tubes are notoriously difficult, as are systems with differential constraints, because the tree grows inefficiently at the boundaries. Here we present a new sampling strategy for the RRT algorithm, based on an estimated feasibility set, which affords a dramatic improvement in performance in these severely constrained systems. We demonstrate the algorithm with a detailed look at the expansion of an RRT in a swing up task, and on path planning for a nonholonomic car.United States. Defense Advanced Research Projects Agency (Learning Locomotion program (AFRL contract # FA8650-05-C-7262)

Reliable Dynamic Motions for a Stiff Quadruped

We present a kinodynamic planning methodology for a high-impedance quadruped robot to negotiate a wide variety of terrain types with high reliability. We achieve motion types ranging from dynamic, double-support lunges for efficient locomotion over extreme obstacles to careful, deliberate foothold and body pose selections which allow for precise foothold placement on rough or intermittent terrain