GPU-based proximity query processing on unstructured triangular mesh model

This paper presents a novel proximity query (PQ) approach capable to detect the collision and calculate the minimal Euclidean distance between two non-convex objects in 3D, namely the robot and the environment. Such approaches are often considered as computationally demanding problems, but are of importance to many applications such as online simulation of haptic feedback and robot collision-free trajectory. Our approach enables to preserve the representation of unstructured environment in the form of triangular meshes. The proposed PQ algorithm is computationally parallel so that it can be effectively implemented on graphics processing units (GPUs). A GPU-based computation scheme is also developed and customized, which shows >200 times faster than an optimized CPU with single core. Comprehensive validation is also conducted on two simulated scenarios in order to demonstrate the practical values of its potential application in image-guided surgical robotics and humanoid robotic control.published_or_final_versio

Shape Analysis Using Spectral Geometry

Shape analysis is a fundamental research topic in computer graphics and computer vision. To date, more and more 3D data is produced by those advanced acquisition capture devices, e.g., laser scanners, depth cameras, and CT/MRI scanners. The increasing data demands advanced analysis tools including shape matching, retrieval, deformation, etc. Nevertheless, 3D Shapes are represented with Euclidean transformations such as translation, scaling, and rotation and digital mesh representations are irregularly sampled. The shape can also deform non-linearly and the sampling may vary. In order to address these challenging problems, we investigate Laplace-Beltrami shape spectra from the differential geometry perspective, focusing more on the intrinsic properties. In this dissertation, the shapes are represented with 2 manifolds, which are differentiable. First, we discuss in detail about the salient geometric feature points in the Laplace-Beltrami spectral domain instead of traditional spatial domains. Simultaneously, the local shape descriptor of a feature point is the Laplace-Beltrami spectrum of the spatial region associated to the point, which are stable and distinctive. The salient spectral geometric features are invariant to spatial Euclidean transforms, isometric deformations and mesh triangulations. Both global and partial matching can be achieved with these salient feature points. Next, we introduce a novel method to analyze a set of poses, i.e., near-isometric deformations, of 3D models that are unregistered. Different shapes of poses are transformed from the 3D spatial domain to a geometry spectral one where all near isometric deformations, mesh triangulations and Euclidean transformations are filtered away. Semantic parts of that model are then determined based on the computed geometric properties of all the mapped vertices in the geometry spectral domain while semantic skeleton can be automatically built with joints detected. Finally we prove the shape spectrum is a continuous function to a scale function on the conformal factor of the manifold. The derivatives of the eigenvalues are analytically expressed with those of the scale function. The property applies to both continuous domain and discrete triangle meshes. On the triangle meshes, a spectrum alignment algorithm is developed. Given two closed triangle meshes, the eigenvalues can be aligned from one to the other and the eigenfunction distributions are aligned as well. This extends the shape spectra across non-isometric deformations, supporting a registration-free analysis of general motion data

Simulating a Pipelined Reconfigurable Mesh on a Linear Array with a Reconfigurable Pipelined Bus System

Due to the unidirectional nature of propagation and predictable delays, optically pipelined buses have been gaining more attention. There have been many models proposed over time that use reconfigurable optically pipelined buses. The reconfigurable nature of the models makes them capable of changing their component’s functionalities and structure that connects the components at every step of computation. There are both one dimensional as well as k –dimensional models that have been proposed in the literature. Though equivalence between various one dimensional models and equivalence between different two dimensional models had been established, so far there has not been any attempt to explore the relationship between a one dimensional model and a two dimensional model. In the proposed research work it is shown that a move from one to two or more dimensions does not cause any increase in the volume of communication between the processors as they communicate in a pipelined manner on the same optical bus. When moving from two dimensions to one dimension, the challenge is to map the processors so that those belonging to a two-dimensional bus segment are contiguous and in the same order on the one-dimensional model. This does not increase any increase in communication overhead as the processors instead of communicating on two dimensional buses now communicate on a linear one dimensional bus structure. To explore the relationship between one dimensional and two dimensional models a commonly used model Linear Array with a Reconfigurable Pipelined Bus System (LARPBS) and its two dimensional counterpart Pipelined Reconfigurable Mesh (PR-Mesh) are chosen Here an attempt has been made to present a simulation of a two dimensional PR-Mesh on a one dimensional LARPBS to establish complexity of the models with respect to one another, and to determine the efficiency with which the LARPBS can simulate the PR-Mesh

Multiple Biolgical Sequence Alignment: Scoring Functions, Algorithms, and Evaluations

Aligning multiple biological sequences such as protein sequences or DNA/RNA sequences is a fundamental task in bioinformatics and sequence analysis. These alignments may contain invaluable information that scientists need to predict the sequences\u27 structures, determine the evolutionary relationships between them, or discover drug-like compounds that can bind to the sequences. Unfortunately, multiple sequence alignment (MSA) is NP-Complete. In addition, the lack of a reliable scoring method makes it very hard to align the sequences reliably and to evaluate the alignment outcomes. In this dissertation, we have designed a new scoring method for use in multiple sequence alignment. Our scoring method encapsulates stereo-chemical properties of sequence residues and their substitution probabilities into a tree-structure scoring scheme. This new technique provides a reliable scoring scheme with low computational complexity. In addition to the new scoring scheme, we have designed an overlapping sequence clustering algorithm to use in our new three multiple sequence alignment algorithms. One of our alignment algorithms uses a dynamic weighted guidance tree to perform multiple sequence alignment in progressive fashion. The use of dynamic weighted tree allows errors in the early alignment stages to be corrected in the subsequence stages. Other two algorithms utilize sequence knowledge-bases and sequence consistency to produce biological meaningful sequence alignments. To improve the speed of the multiple sequence alignment, we have developed a parallel algorithm that can be deployed on reconfigurable computer models. Analytically, our parallel algorithm is the fastest progressive multiple sequence alignment algorithm

Simulations and Algorithms on Reconfigurable Meshes With Pipelined Optical Buses.

Recently, many models using reconfigurable optically pipelined buses have been proposed in the literature. A system with an optically pipelined bus uses optical waveguides, with unidirectional propagation and predictable delays, instead of electrical buses to transfer information among processors. These two properties enable synchronized concurrent access to an optical bus in a pipelined fashion. Combined with the abilities of the bus structure to broadcast and multicast, this architecture suits many communication-intensive applications. We establish the equivalence of three such one-dimensional optical models, namely the LARPBS, LPB, and POB. This implies an automatic translation of algorithms (without loss of speed or efficiency) among these models. In particular, since the LPB is the same as an LARPBS without the ability to segment its buses, their equivalence establishes reconfigurable delays (rather than segmenting ability) as the key to the power of optically pipelined models. We also present simulations for a number of two-dimensional optical models and establish that they possess the same complexity, so that any of these models can simulate a step of one of the other models in constant time with a polynomial increase in size. Specifically, we determine the complexity of three two-dimensional optical models (the PR-Mesh, APPBS, and AROB) to be the same as the well known LR-Mesh and the cycle-free LR-Mesh. We develop algorithms for the LARPBS and PR-Mesh that are more efficient than existing algorithms in part by exploiting the pipelining, segmenting, and multicasting characteristics of these models. We also consider the implications of certain physical constraints placed on the system by restricting the distance over which two processors are able to communicate. All algorithms developed for these models assume that a healthy system is available. We present some fundamental algorithms that are able to tolerate up to N/2 faults on an N-processor LARPBS. We then extend these results to apply to other algorithms in the areas of image processing and matrix operations

A Sampling-Based Tree Planner for Robot Navigation Among Movable Obstacles

This thesis proposes a planner that solves Navigation Among Movable Obstacles problems giving robots the ability to reason about the environment and choose when manipulating obstacles. The planner combines the A*-Search and the exploration strategy of the Kinodynamic Motion Planning by Interior-Exterior Cell Exploration algorithm. It is locally optimal and independent from the size of the map and from the number, shape, and position of obstacles. It assumes full world knowledgeope

Pouch Motors: Printable Soft Actuators Integrated with Computational Design

We propose pouch motors, a new family of printable soft actuators integrated with computational design. The pouch motor consists of one or more inflatable gas-tight bladders made of sheet materials. This printable actuator is designed and fabricated in a planar fashion. It allows both easy prototyping and mass fabrication of affordable robotic systems. We provide theoretical models of the actuators compared with the experimental data. The measured maximum stroke and tension of the linear pouch motor are up to 28% and 100 N, respectively. The measured maximum range of motion and torque of the angular pouch motor are up to 80° and 0.2 N, respectively. We also develop an algorithm that automatically generates the patterns of the pouches and their fluidic channels. A custom-built fabrication machine streamlines the automated process from design to fabrication. We demonstrate a computer-generated life-sized hand that can hold a foam ball and perform gestures with 12 pouch motors, which can be fabricated in 15 min.National Science Foundation (U.S.) (1240383)National Science Foundation (U.S.) (1138967)United States. Department of Defens

Cognitive Task Planning for Smart Industrial Robots

This research work presents a novel Cognitive Task Planning framework for Smart Industrial Robots. The framework makes an industrial mobile manipulator robot Cognitive by applying Semantic Web Technologies. It also introduces a novel Navigation Among Movable Obstacles algorithm for robots navigating and manipulating inside a firm. The objective of Industrie 4.0 is the creation of Smart Factories: modular firms provided with cyber-physical systems able to strong customize products under the condition of highly flexible mass-production. Such systems should real-time communicate and cooperate with each other and with humans via the Internet of Things. They should intelligently adapt to the changing surroundings and autonomously navigate inside a firm while moving obstacles that occlude free paths, even if seen for the first time. At the end, in order to accomplish all these tasks while being efficient, they should learn from their actions and from that of other agents. Most of existing industrial mobile robots navigate along pre-generated trajectories. They follow ectrified wires embedded in the ground or lines painted on th efloor. When there is no expectation of environment changes and cycle times are critical, this planning is functional. When workspaces and tasks change frequently, it is better to plan dynamically: robots should autonomously navigate without relying on modifications of their environments. Consider the human behavior: humans reason about the environment and consider the possibility of moving obstacles if a certain goal cannot be reached or if moving objects may significantly shorten the path to it. This problem is named Navigation Among Movable Obstacles and is mostly known in rescue robotics. This work transposes the problem on an industrial scenario and tries to deal with its two challenges: the high dimensionality of the state space and the treatment of uncertainty. The proposed NAMO algorithm aims to focus exploration on less explored areas. For this reason it extends the Kinodynamic Motion Planning by Interior-Exterior Cell Exploration algorithm. The extension does not impose obstacles avoidance: it assigns an importance to each cell by combining the efforts necessary to reach it and that needed to free it from obstacles. The obtained algorithm is scalable because of its independence from the size of the map and from the number, shape, and pose of obstacles. It does not impose restrictions on actions to be performed: the robot can both push and grasp every object. Currently, the algorithm assumes full world knowledge but the environment is reconfigurable and the algorithm can be easily extended in order to solve NAMO problems in unknown environments. The algorithm handles sensor feedbacks and corrects uncertainties. Usually Robotics separates Motion Planning and Manipulation problems. NAMO forces their combined processing by introducing the need of manipulating multiple objects, often unknown, while navigating. Adopting standard precomputed grasps is not sufficient to deal with the big amount of existing different objects. A Semantic Knowledge Framework is proposed in support of the proposed algorithm by giving robots the ability to learn to manipulate objects and disseminate the information gained during the fulfillment of tasks. The Framework is composed by an Ontology and an Engine. The Ontology extends the IEEE Standard Ontologies for Robotics and Automation and contains descriptions of learned manipulation tasks and detected objects. It is accessible from any robot connected to the Cloud. It can be considered a data store for the efficient and reliable execution of repetitive tasks; and a Web-based repository for the exchange of information between robots and for the speed up of the learning phase. No other manipulation ontology exists respecting the IEEE Standard and, regardless the standard, the proposed ontology differs from the existing ones because of the type of features saved and the efficient way in which they can be accessed: through a super fast Cascade Hashing algorithm. The Engine lets compute and store the manipulation actions when not present in the Ontology. It is based on Reinforcement Learning techniques that avoid massive trainings on large-scale databases and favors human-robot interactions. The overall system is flexible and easily adaptable to different robots operating in different industrial environments. It is characterized by a modular structure where each software block is completely reusable. Every block is based on the open-source Robot Operating System. Not all industrial robot controllers are designed to be ROS-compliant. This thesis presents the method adopted during this research in order to Open Industrial Robot Controllers and create a ROS-Industrial interface for them