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A Metaheuristic Algorithm for the Fleet Size and Mix Vehicle Routing Problem with Pickups and Deliveries
No full textAbstract
This thesis addresses an extended variant of the fleet size and mix vehicle routing problem with aspects such as split pickups and deliveries, different loading and unloading methods, and the charging of electric vehicles. The aim of the work has been to be able to efficiently solve large-scale instances of the problem based on real data. To tackle this objective, a metaheuristic algorithm has been developed based on the adaptive large neighborhood search framework. A procedure for destroying and repairing a solution has been designed and implemented such that the challenging aspects of the problem definition are handled appropriately. Moreover, the use of simulated annealing and the technique of applying noise to diversify the search have been explored. The algorithm was run on three realistic instances, in a set of shorter runs to investigate the effect of adding noise and using simulated annealing. Then, three relatively long runs were conducted to obtain definitive solutions to the instances. The algorithm managed to find a promising solutions to all three instances, and the objective value of the best solutions found were significantly lower than the objective values of the initial solutions
Developing a ROS2 infrastructure and control system
No full textThe increasing complexity of industrial automation demands agile and adaptive control systems capable of dynamic task execution. This thesis addresses these challenges by developing a ROS2-based infrastructure and control system for autonomous robots in a simulated factory environment, aligned with the Agile Robotics for Industrial Automation Competition (ARIAC) 2024. The proposed solution integrates an operation runner for task coordination and Convolutional Neural Network (CNN) for real-time part classification, aiming to optimize adaptability and efficiency in a dynamic manufacturing setting.
The control system leverages ROS2’s communication framework such as topics and services to manage Automated Guided Vehicle (AGV), robotic arms, and competition infrastructure such as orders. The operation runner dynamically coordinate tasks by evaluating preconditions and postconditions of executable operations, enabling scalable control of multiple robots. A CNN, trained on HSV-masked and augmented image data, achieves robust part classification despite variations in orientation. The operation runner demonstrated success in AGV coordination and scalability, while the CNN demonstrates real-time capabilities with classification tasks. However, the integration of the control system and vision components together and into the ARIAC competition framework was not fully realized, mainly due to time constraints and technical challenges
Efficiently Calculating Relaxation Errors
No full textRelaxed data structures have been designed to leverage the parallelism of modern processors more effectively than current strict concurrent data structures can. This kind of data structure relaxes the semantics for performance at the cost of correctness. For instance, to avoid contention between threads, a relaxed FIFO queue may return an element close to the head rather than the head itself. This out-of-order operation can be measured through relaxation errors, most notably rank errors. A current problem within the field of relaxed data structures is that the process of computing rank errors is rarely discussed, and only final results are presented. Furthermore, the methods presented are inefficient and require computationally intensive calculations. Therefore, there is a need in the field for faster and more efficient algorithms to compute rank errors. In this thesis, we present several approaches and algorithms for calculating the rank errors of FIFO (First-In-First-Out) queues and benchmark them against one another. Specifically, we introduce two algorithms that are hundreds of times faster than the current methods in the field. Additionally, the best-performing algorithms are adapted to calculate delay errors for FIFO queues and rank errors for LIFO (Last-In-First-Out) queues, demonstrating that their performance can be extended to other neighboring problems. Finally, we implement approximations of the calculations to enhance performance at the cost of correctness
Utveckling och implementering av kontrollytor för en räddningsdrönare
No full textUnder ett masterarbete vid Institutionen för mekanik och maritima vetenskaper på Chalmers tekniska högskola utvecklades en drönare för Sjöräddningssällskapet. Under en testflygning förlorade dock drönaren kontrollen och kraschade. Under de efterföljande åren har flera kandidatarbeten genomförts med syftet att förbättra prestandan och styrbarheten hos den tidigare utvecklade drönaren. Trots lovande förbättringsförslag har ingen av dessa koncept ännu testats i en kombinerad, fungerande prototyp.
Målet med detta kandidatarbete var att implementera och modifiera de kontrollytor som föreslagits i tidigare kandidatarbeten. För att utvärdera de nya konfigurationerna genomfördes simuleringar i OpenVSP samt vindtunneltester. CFD-resultaten visade på en ökning av både pitch- och rollmoment, vilket tyder på förbättrad manövrerbarhet. Vindtunneltesterna visade däremot avsevärt mindre momentvärden jämfört med simuleringarna. Denna avvikelse kan bero på begränsningar i OpenVSP, som inte tar hänsyn till stall eller viskösa effekter
High-Precision Positioning of Known Objects Using a Static Monocular Camera
No full textAbstract
Accurate perception of the internal vehicle environment is essential for occupant safety, enabling timely and coordinated system responses in critical situations. While advanced perception systems based on deep learning have shown strong performance, they often require high computational and financial resources. This thesis explores classical, image-based object detection methods using a static monocular camera as a lightweight and cost-effective alternative. The focus is on precise localization of the steering wheel as a dynamic object in a static in-cabin environment. Although the camera is fixed, the setup is interpreted as a reverse scenario of moving camera and static object, meaning the object motion simulates camera movement. By tracking keypoint displacement across frames, the corresponding camera motion is inferred. The methodology includes image preprocessing for distortion correction and enhancement, evaluation of classical methods for feature extraction and matching, camera motion estimation using a visual odometry pipeline, and triangulationbased
3D reconstruction of 2D image points. Among the tested methods, ORB-BF and Lucas-Kanade (LK) show superior performance in keypoint detection, matching, and motion vector extraction. ORB-BF is used for consistent keypoint matching, while LK provides displacement vectors, both essential for pose estimation and 3D localization. The resulting pipeline is interpretable, computationally efficient, and well-suited for low-power, cost-sensitive in-cabin monitoring systems. Overall, the results confirm that reliable object localization is achievable using only a single monocular camera. However, the absence of real-world measurements, such as known object dimensions and camera intrinsics, limits the full validation of displacement and depth estimations
High Voltage Transformer Bushings: Model To App
No full textAbstract
Transformer bushings play a critical role in ensuring the efficient and safe operation of power transformers. Understanding the electrical and thermal behavior of these components is essential for optimizing their design and performance. Therefore the main outline of the thesis is to develop a comprehensive analysis application for transformer bushings using COMSOL Multiphysics software. The application integrates electrical and thermal simulations to provide a holistic understanding of bushing performance under various geometric parameters. The thesis discusses the modelling approach, including the incorporation of complex material properties and boundary conditions. Furthermore, it highlights the transition from the initial computational model to a user friendly application interface, allowing engineers and designers to efficiently analyze and optimize the performance of transformer bushings
Surface coating on cathode materials for environmental-friendly battery manufacturing
No full textAn increasing need for sustainable energy has put lithium-ion battery in the forefront of the energy race. Traditional batteries cannot meet the energy demands of the future. Moreover, the use of toxic N-Methyl-2-pyrrolidone (NMP) solvent causes high energy consumption, high cost, and environmental concern of the current battery manufacturing process. In order to eliminate the use of NMP solvent during the electrode processing, here the aim of the project is to modify the surface of cathode material and make it favourable for the water-based electrode processing. Considering the stability issue of cathode in water, graphene, which is impermeable to water, was used as coating materials to protect the surface of cathode material. In addition, introducing graphene in the Li-ion battery improves the performance of the battery as it enhances the conductivity and increases the surface area. The graphene-coated cathode materials were characterized by Scanning Electron Microscopy (SEM) and Thermogravimetric Analysis (TGA). The preliminary results demonstrated that the graphene coating could improve the cycling stability and increase the capacity of the lithium-ion battery
Numerical Methods for mapping band-type resonance in insect flight
No full textInsect flight is a highly complex and energy-intensive process. Flapping-wing insects employ a
unique muscle contraction mechanism that enables high-frequency wing beats, with metabolic rates
reaching several times those at rest. Their remarkable endurance during flight highlights the
importance of understanding the energy optimization involved. This thesis focuses on developing
numerical methods to map band-type resonance, which serves as a benchmark for assessing
whether a system achieves an energy-optimal state. We describe the mapping of band-type
resonance as an optimization problem and propose two primary numerical methods: particle swarm
optimization and numerical continuation. We evaluate the accuracy of the numerical solutions via
the solution work loops and power waveforms and compare them with analytical approximations to
the space of band-type resonant states. Our findings reveal that while the standalone particle swarm
method can provide a relatively complete set of estimated solutions, the solution space lacks
continuity. The numerical continuation method sacrifices some completeness in finding solution
sets to ensure better continuity in the corresponding domain of the output solution set.
After comparing these methods' performance in identifying potential solutions for simple cases, we
improve them and propose a compound numerical method for solving more complex problems,
such as higher harmonic and nonlinear oscillators. Notably, this compound algorithm performs well
not only on simple linear cases with known analytical solutions but also on complex problems
lacking analytical solutions, offering a valuable numerical tool for estimating the mapping zone of
band-type resonance when analytical methods are not feasible.
Comparing the results of mapping zones of band-type resonance with wingbeat frequency
modulation behaviour observed in actual insect species suggests that such behaviour may be
consistent with sustained resonant energy savings by exploiting band-type resonance.
This report is written in English
A sustainable work environment? Exploring harmonies and tensions in the role of sustainability leaders in architectural and building consultancy firms
No full textSustainability leaders are leading the development toward a sustainable society.
Their responsibilities are constantly increasing with the growing demand for exper-
tise in all parts of the organisations. Previous studies have examined how the role
has evolved and the challenges they experience. However, the effect on their work
environment and their view of the role remains unclear. This thesis aims to inves-
tigate the harmonies and tensions that sustainability leaders in consultancy firms
within the building sector experience with a focus on organisational structures and
practices. Highlighting what should be nurtured or improved expands the basis for
how the role could develop in the future. An abductive qualitative approach was
applied, based on semi-structured interviews with nine sustainability leaders and
two HR professionals. The collected data were analysed with activity theory with
focus on tensions and the complemented concept of harmonies. The findings in-
dicate harmonies relating to inter-organisational networks and leaders’ passion for
sustainability work, as well as tensions relating to increasing responsibilities, the
broad need for expertise, limited personnel resources and challenges relating to the
consultancy profession. The relationship between creativity and sustainability work
is explored, and structures that promote or inhibit both are discussed. It is con-
cluded that sustainability leaders are drawn to a creative and innovative profession
that is transforming toward a more controlling function with increasing reporting
demands, which decreases flexibility and creative space within the role. To ensure a
sustainable work environment for sustainability leaders, their networks and passion
should be nurtured, and consideration should be given to the tension between their
expectations of the role, what they want to accomplish, and the direction in which
the role is developing. The resources allocated to them should reflect the scale of
their responsibilities, and the relationships with management and colleagues develop
to ensure supportive, collaborative structures within the organisation.
Keywords: sustainability leader, work environment, organisational structures, prac-
tices, creativity, activity theory, harmonies, tensions