22 research outputs found
DandeBot - An Autonomous Weeding Solution for Residential Lawns
No full textDandeBot – An Autonomous Weeding Solution for Residential Lawns
Author: Nishanth Rajkumar
This thesis presents the development and validation of DandeBot, an autonomous robotic system designed for comprehensive residential lawn maintenance. The robot addresses the need for efficient, eco-conscious, and low maintenance lawn care through a fully electric platform powered by an AI-driven software stack. Emphasizing safety, adaptability, and ease of use, the hardware was developed using CAD and Design for Manufacturing (DFM) principles, resulting in a modular and robust design. The integrated software stack combines localization, mapping, and path planning using odometry, visual odometry, and IMU data fusion to navigate dynamic outdoor environments. Task-specific algorithms were developed and validated for autonomous navigation, weed detection, and obstacle avoidance. Key hardware innovations include a modular gripper system for weed removal and adaptable attachments for multiple lawn care tasks. Field trials confirmed the robot’s capability to perform with high precision and reliability in varied lawn conditions, significantly reducing the need for human intervention. This work contributes to the growing field of service robotics by demonstrating how intelligent systems can automate routine household maintenance. The thesis concludes by outlining future research directions, including system scalability, enhanced multi-tasking capabilities, and integration with smart home networks
Testing properties of Ising models
No full textThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.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 (pages 99-102).Given samples from an unknown multivariate distribution p, is it possible to distinguish whether p is the product of its marginals versus p being [epsilon]-far from every product distribution? Similarly, is it possible to distinguish whether p equals a given distribution q versus p and q being [epsilon]-far from each other? These problems of testing independence and goodness-of- fit have received enormous attention in statistics, information theory, and theoretical computer science, with sample-optimal algorithms known in several interesting regimes of parameters [14, 15, 17, 18, 20]. Unfortunately, it has also been understood that these problems become intractable in large dimensions, necessitating exponential sample complexity. Motivated by the exponential lower bounds for general distributions as well as the ubiquity of Markov Random Fields (MRFs) in the modeling of high-dimensional distributions, we study distribution testing on structured multivariate distributions, and in particular the prototypical example of MRFs: the Ising Model. We demonstrate that, in this structured setting, we can avoid the curse of dimensionality, obtaining sample and time efficient testers for independence and goodness-of-fit which yield a sample complexity of poly(n)=[epsilon]2 on n-node Ising models. Along the way, we develop new tools for establishing concentration of functions of the Ising model, using the exchangeable pairs framework developed by Chatterjee [27], and improving upon this framework. In particular, we prove tighter concentration results for multi-linear functions of the Ising model in the high-temperature regime. We also prove a lower bound of n=[epsilon] on the sample complexity required for testing uniformity and independence of n-node Ising models.by Sai Nishanth Dikkala.S.M
Predictive and prescriptive methods in operations research and machine learning : an optimization approach
No full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 213-221).The availability and prevalence of data have provided a substantial opportunity for decision makers to improve decisions and outcomes by effectively using this data. In this thesis, we propose approaches that start from data leading to high-quality decisions and predictions in various application areas. In the first chapter, we consider problems with observational data, and propose variants of machine learning (ML) algorithms that are trained by taking into account decision quality. The traditional approach to such a task has often focused on two-steps, separating the estimation task from the subsequent optimization task which uses these estimated models. Consequently, this approach can miss out on potential improvements in decision quality by considering these tasks jointly. Crucially, this leads to stronger prescriptive performance, particularly for smaller training set sizes, and improves the decision quality by 3 - 5% over other state-of-the-art methods.We introduce the idea of uncertainty penalization to control the optimism of these methods which improves their performance, and propose finite-sample regret bounds. Through experiments on real and synthetic data sets, we demonstrate the value of this approach. In the second chapter, we consider observational data with decision-dependent uncertainty; in particular, we focus on problems with a finite number of possible decisions (treatments). We present our method of prescriptive trees, that prescribes the best treatment option by learning from observational data while simultaneously predicting counterfactuals. We demonstrate the effectiveness of such an approach using real data for the problem of personalized diabetes management. In the third chapter, we consider stochastic optimization problems when the sample average approximation approach is computationally expensive.We introduce a novel measure, called the Prescriptive divergence which takes into account the decision quality of the scenarios, and consider scenario reduction in this context. We demonstrate the power of this optimization-based approach on various examples. In the fourth chapter, we present our work on a problem in predictive analytics where we focus on ML problems from a modern optimization perspective. For sparse shape-constrained regression problems, we propose modern optimization based algorithms that are scalable, and recover the true support with high accuracy and low false positive rates.by Nishanth Mundru.Ph. D.Ph.D. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Cente
Energy extraction, or lack thereof
No full textThe problem of stability of rotating black holes is the subject of a long standing research program since the 1960s and remains an unresolved problem in general relativity. A major obstacle in the black hole stability problem is that the energy of waves propagating through rotating black holes spacetimes is not necessarily positive-definite, due to the so called ergo-region. This is a serious complication that limits the efficacy of most mathematical techniques. In this expository article, we report that, despite the ergo-region, there exists a positive-definite total energy for axisymmetric Maxwell, gravitational and electrovacuum perturbations of Kerr and Kerr–Newman black hole spacetimes. © 2023, The Author(s)
RDMA based IP routing protocols and router architecture
No full textThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and COmputer Engineering.Includes bibliographic references (leaves 75-77)The Ethernet technology has advanced from the era of fast Ethernet to the era of gigabit ethernet. The gigabit routers currently available in the market are employing expensive hardware based implementations for improving the throughput [6], which makes the overall cost of the device prohibitively high. In this thesis the author reviews the existing router architectures and routing protocols and critiques the shortcomings of the existing implementation. This thesis evaluates the drawbacks in the existing infrastructure and proposes an architecture that provides a solution based on the RDMA protocol. The proposed architecture uses the RDMA protocol for transferring the data payload from the ingress interface to the destination interface. In this research the author also presents an analytical mathematical model that can be used for calculating the delay incurred by a packet, memory utilization and CPU utilization for both architectures. The potential benefits by the use of RDMA protocol are also explained in detail in this thesis. The necessity for modifying the update packet structure in the existing implementation of RIP is discussed in detail. Packet payload handling in both architectures is compared and the advantages in the RDMA protocol based implementation are presented
Liquid slip/stick over hydrophobic/hydrophilic surfaces and their implications in coating processes
No full textFluid slip has been observed experimentally in micro- and nanoscale liquid flow devices by several investigators. While observations of fluid slip continue to expand, the generating mechanism responsible for fluid slip is not well understood and indeed generalized mathematical formulation is not available. In the present paper, the author gave an attempt to explain the generating mechanism for the fluid slip on hydrophobic surface. The importance of the present theory lies in the fact that it obviates the need to impose the ad hoc Newtons slip at the fluid-wall interface and also the pre-assumption of thin gas layer close to the wall. Surface interactions with the liquid/fluid at molecular scale are incorporated together with the phase field theory to accurately predict the phase of the fluid close to the wall, which is imperative to accurately determine the fluid slip close to the wall. It is noticed that the incorporation of these molecule-surface interactions have significant effect on the resulting coating windows on both hydrophobic and hydrophilic substrates, however it is more predominant for the hydrophobic one
Um modelo para provisão de garantia dinâmica de tempo real em middleware baseado em componentes
No full textTese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2007.A abordagem baseada em componentes foi desenvolvida em resposta à necessidade de lidar com a complexidade das aplicações e diminuir o ciclo de desenvolvimento do software. A separação em lógica de aplicação e parte não funcional em um componente permite que requisitos temporais sejam configurados, ao invés de inseridos ao longo do código. Como resultado, os componentes se tornam menos dependentes da plataforma subjacente e podem ser reusados em aplicações diferentes. Este trabalho apresenta um modelo para provisão de garantia dinâmica em sistemas de tempo real distribuídos baseados em componentes. O modelo desenvolvido condiciona a aceitação de um cliente à disponibilidade de recursos para satisfazer os requisitos temporais deste cliente e de clientes previamente aceitos. Este modelo permite a adoção de diferentes algoritmos para o teste de aceitação, se adequando ao modelo das tarefas escalonadas ou à capacidade da plataforma. Outra contribuição é um serviço de monitoramento de tempos de resposta de componentes, inicialmente desenvolvidos para prover dados iniciais para o modelo de garantia dinâmica. O serviço de monitoramento permite que o mecanismo de garantia dinâmica se mantenha preciso apesar da flutuação da carga computacional do servidor e permite a aplicação de algoritmos probabilistas para o modelo de garantia dinâmica.Abstract : The component-based approach was developed in response to the need to cope with application complexity and reduce the software development time. The component separation of concerns allows real-time constraints to be configured instead of hard coded. As a result, components become less dependent from the underlying platform and can be reused in different applications. This work presentes a model for real-time dynamic guarantee for component-based distributed systems. According to the model, the acceptance of a client to the system is subject to the availability of resources to satisfy all clients real-time constraints. This model allows the use of different algorithms for the acceptance test, according to the application task model or the platform capacity. Another contribution is the response time monitoring service, developed to provide input data for the dynamic guarantee model. This service provides updates for the dynamic guarantee model and also allows the use of probabilistic approaches for the acceptance test
Design and Fabrication of Nylon/Teflon Die Set for Spherical Moulding.
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
