Visual Simultaneous Localization And Mapping (SLAM) allows for three dimensionalreconstruction from a camera’s output and simultaneous positioning of the camera withinthe reconstruction. With use cases ranging from autonomous vehicles to augmentedreality, the SLAM field has garnered interest both commercially and academically. A SLAM system performs odometry as it estimates the camera’s movement throughthe scene. The incremental estimation of odometry is not error free and exhibits driftover time with map inconsistencies as a result. Detecting the return to a previously seenplace, a loop, means that this new information regarding our position can be incorporatedto correct the trajectory retroactively. Loop detection can also facilitate relocalization ifthe system loses tracking due to e.g. heavy motion blur. This thesis proposes an odometric system making use of bundle adjustment within akeyframe based stereo SLAM application. This system is capable of detecting loops byutilizing the algorithm FAB-MAP. Two aspects of this system is evaluated, the odometryand the capability to relocate. Both of these are evaluated using the EuRoC MAV dataset,with an absolute trajectory RMS error ranging from 0.80 m to 1.70 m for the machinehall sequences. The capability to relocate is evaluated using a novel methodology that intuitively canbe interpreted. Results are given for different levels of strictness to encompass differentuse cases. The method makes use of reprojection of points seen in keyframes to definewhether a relocalization is possible or not. The system shows a capability to relocate inup to 85% of all cases when a keyframe exists that can project 90% of its points intothe current view. Errors in estimated poses were found to be correlated with the relativedistance, with errors less than 10 cm in 23% to 73% of all cases. The evaluation of the whole system is augmented with an evaluation of local imagedescriptors and pose estimation algorithms. The descriptor SIFT was found to performbest overall, but demanding to compute. BRISK was deemed the best alternative for afast yet accurate descriptor. Conclusions that can be drawn from this thesis is that FAB-MAP works well fordetecting loops as long as the addition of keyframes is handled appropriately.

We have written an optimising compiler for a typeless, imperative, modular programming language. The optimiser, which works on a 3-address intermediate representation generated from the source program, uses some novel techniques described in this thesis. The techniques are universally applicable, although some are particularly useful in typeless compilation. We present a new register allocation and assignment scheme. Unlike traditional "colouring" allocators, our method separates the problem into distinct allocation and assignment phases. The former is achieved by using an iterative process to extend a local (within basic blocks) allocation method to the global (across basic blocks) domain. This obviates the need for a sophisticated assignment algorithm; we show how to use simple heuristics to assign registers after allocation. We also present a simple method for identifying loops in a program's intermediate representation and assigning loop nesting levels. Unlike traditional methods, this does not rely on the concept of flowgraph dominators, and is able to deal sensibly with irreducible flowgraphs and "unstructured" loops that interlock or partially overlap. The major part of the thesis concerns value range analysis. Based on the theoretical framework of abstract interpretation, we describe an analysis of the intermediate code that predicts safe approximations to the run-time value ranges of variables and memory used by the program being compiled. To be useful in compiling a typeless language, this analysis must be able to handle values of different kinds (integers, pointers, function addresses, etc.) We show how we can subsume some traditional optimisation techniques, such as constant propagation, into more powerful methods that take advantage of value range information to optimise a wider variety of cases. We also show how this information can be used to recover most of the benefits of types, without sacrificing the flexibility of typelessness. Besides the above, value range analysis allows a number of optimisations that were heretofore impossible. Many of these are improvements to register allocation; we investigate better treatments for variables that can be accessed by address. We also describe a method of removing memory accesses by allowing variables that are simultaneously live to share registers, and suggest a similar scheme for values stored in memory. Finally, we show how the results of value range analysis can be shared across different program modules and different compiler runs. The method used is powerful enough to be useful, but simple enough to integrate with old code that cannot be recompiled. Inter-modular optimisation can be transparent to the user, improving the results of value range analysis within a module without altering its functionality; or it can be visible, optimising modules with respect to each other.

abstract: Tolerance specification for manufacturing components from 3D models is a tedious task and often requires expertise of “detailers”. The work presented here is a part of a larger ongoing project aimed at automating tolerance specification to aid less experienced designers by producing consistent geometric dimensioning and tolerancing (GD&T). Tolerance specification can be separated into two major tasks; tolerance schema generation and tolerance value specification. This thesis will focus on the latter part of automated tolerance specification, namely tolerance value allocation and analysis. The tolerance schema (sans values) required prior to these tasks have already been generated by the auto-tolerancing software. This information is communicated through a constraint tolerance feature graph file developed previously at Design Automation Lab (DAL) and is consistent with ASME Y14.5 standard. The objective of this research is to allocate tolerance values to ensure that the assemblability conditions are satisfied. Assemblability refers to “the ability to assemble/fit a set of parts in specified configuration given a nominal geometry and its corresponding tolerances”. Assemblability is determined by the clearances between the mating features. These clearances are affected by accumulation of tolerances in tolerance loops and hence, the tolerance loops are extracted first. Once tolerance loops have been identified initial tolerance values are allocated to the contributors in these loops. It is highly unlikely that the initial allocation would satisfice assemblability requirements. Overlapping loops have to be simultaneously satisfied progressively. Hence, tolerances will need to be re-allocated iteratively. This is done with the help of tolerance analysis module. The tolerance allocation and analysis module receives the constraint graph which contains all basic dimensions and mating constraints from the generated schema. The tolerance loops are detected by traversing the constraint graph. The initial allocation distributes the tolerance budget computed from clearance available in the loop, among its contributors in proportion to the associated nominal dimensions. The analysis module subjects the loops to 3D parametric variation analysis and estimates the variation parameters for the clearances. The re-allocation module uses hill climbing heuristics derived from the distribution parameters to select a loop. Re-allocation Of the tolerance values is done using sensitivities and the weights associated with the contributors in the stack. Several test cases have been run with this software and the desired user input acceptance rates are achieved. Three test cases are presented and output of each module is discussed. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

This dissertation is concerned with three-dimensional (3D) sensing and 3D scan representation. Three-dimensional records are important tools in several disciplines; such as medical imaging, archaeology, and mobile robotics. This dissertation proposes the normal-distributions transform, NDT, as a general 3D surface representation with applications in scan registration, localisation, loop detection, and surface-structure analysis. After applying NDT, the surface is represented by a smooth function with analytic derivatives. This representation has several attractive properties. The smooth function representation makes it possible to use standard numerical optimisation methods, such as Newton’s method, for 3D registration. This dissertation extends the original two-dimensional NDT registration algorithm of Biber and Straßer to 3D and introduces a number of improvements. The 3D-NDT scan-registration algorithm is compared to current de facto standard registration algorithms. 3D-NDT scan registration with the proposed extensions is shown to be more robust, more accurate, and faster than the popular ICP algorithm. An additional benefit is that 3D-NDT registration provides a confidence measure of the result with little additional effort. Furthermore, a kernel-based extension to 3D-NDT for registering coloured data is proposed. Approaches based on local visual features typically use only a small fraction of the available 3D points for registration. In contrast, Colour-NDT uses all of the available 3D data. The dissertation proposes to use a combination of local visual features and Colour-NDT for robust registration of coloured 3D scans. Also building on NDT, a novel approach using 3D laser scans to perform appearance-based loop detection for mobile robots is proposed. Loop detection is an importantproblem in the SLAM (simultaneous localisation and mapping) domain. The proposed approach uses only the appearance of 3D point clouds to detect loops and requires nopose information. It exploits the NDT surface representation to create histograms based on local surface orientation and smoothness. The surface-shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. In order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones, the proposed approach uses expectation maximisation to fit a Gamma mixture model to the output similarity measures. In order to enable more high-level tasks, it is desirable to extract semantic information from 3D models. One important task where such 3D surface analysis is useful is boulder detection for mining vehicles. This dissertation presents a method, also inspired by NDT, that provides clues as to where the pile is, where the bucket should be placed for loading, and where there are obstacles. The points of 3D point clouds are classified based on the surrounding surface roughness and orientation. Other potential applications include extraction of drivable paths over uneven surfaces.

This diploma thesis deals with the problem of mobile robot localisation in the environment based on current 2D and 3D sensor data and previous records. Work is focused on detecting previously visited places by robot. The implemented system is suitable for loop detection, using the Gestalt 3D descriptors. The output of the system provides corresponding positions on which the robot was already located. The functionality of the system has been tested and evaluated on LiDAR data.

This work deals with conception and implemetation of tools for finding approximate palindromes in DNA sequences. The work focuses on the description of DNA structure, and on the function of palindromes in DNA sequences, and on the description of methods for finding approximate palindromes. Main part of thesis is focused on conclusion and description of implementation approximate palidromes finding tool.