Development of an Autonomous Vehicle Platform

Autonomous vehicles and their related development are gaining a lot of traction as a promising up and coming technology. The Mechatronics Vehicle Systems lab at the University of Waterloo is well pioneered in the automotive industry and seeks to apply their knowledge and skills to autonomous vehicles. Having an autonomous vehicle development platform at the University allows for development and testing of state of the art algorithms that can potentially benefit the entire automotive industry. An autonomous driving platform based on a Chevrolet Equinox is proposed in this thesis. Various types of sensors are installed on the vehicle and interfaced, allowing for full coverage of the surrounding environment. A software platform is developed which uses ROS and Matlab simultaneously, benefiting from the libraries, tools, and resources that come with both. The hardware platform is designed with simplicity and functionality in mind. Moreover, a simulation platform is used for testing various algorithms before real world implementation. Various types of sensor calibrations are necessary to fully synchronize all the sensors on the platform spatially. A joint calibration method that allows for the simultaneous calibration of all 3D sensors sharing a common field of view is implemented. Specialized hand-eye calibration methods to calibrate the GPS navigation system to the LIDAR and camera sensors are explored. Furthermore, vehicle to everything interfacing is kept in mind and a calibration technique is presented in order to localize infrastructure mounted sensors to a GPS navigation system. The calibration techniques are tested and areas of improvement are revealed. The developed platform is tested with the task of autonomous lane keeping. The steering wheel angle of the vehicle is controlled by the developed algorithm utilizing the camera and GPS navigation solution. The algorithm is tested in simulation with good results. Before real world testing, time synchronization between various devices on the platform, as well as testing of the actuators' controllers is performed. Finally, the lane keeping algorithm is tested on the developed platform on the University of Waterloo Ring Road. The system is able to autonomously steer around the majority of the road which is approximately a 2.5 km distance

Evaluation of Local Kinematic Motion Planning Algorithms for a Truck and Trailer System

Over the past few decades, researchers have worked towards developing autonomous systems that can be used in everyday transportation, and with the emergence of new sensor, hardware, and software technologies, the goal of self-driving vehicles is now on the brink of becoming a reality. In order for these systems to properly plan and react to their complex environments, they need to be equipped with the proper tools and algorithms to ensure safe deployment for all stakeholders. Navigating tight spaces with truck and trailer systems in dynamic environments can be a difficult task due to their nonlinear dynamics, delayed actuation, and large physical dimensions. This thesis presents a kinematic approach to local motion planning for truck and trailer vehicles in the forward motion. This approach was applied to the sample-based planning algorithms RRT* and RRTᵡ in order to adapt and replan in the presence of dynamic obstacles. A combined motion planning and control framework was then developed and deployed in both simulations, using American Truck Simulator, and on an International ProStar 122+ truck. After the feedback controllers were iteratively tuned, the motion planners were evaluated alongside a deterministic Hybrid A* approach using a lane change and seaport scenario with simulated static and dynamic obstacles. In both cases, the approach demonstrated the ability for the sample-based planner approach to provide real-time and feasible plans for the controller to execute at low speeds while maintaining a safe distance away from nearby obstacles

Strategic Latency Unleashed: The Role of Technology in a Revisionist Global Order and the Implications for Special Operations Forces

The article of record may be found at https://cgsr.llnl.govThis work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory in part under Contract W-7405-Eng-48 and in part under Contract DE-AC52-07NA27344. The views and opinions of the author expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC. ISBN-978-1-952565-07-6 LCCN-2021901137 LLNL-BOOK-818513 TID-59693This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory in part under Contract W-7405-Eng-48 and in part under Contract DE-AC52-07NA27344. The views and opinions of the author expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC. ISBN-978-1-952565-07-6 LCCN-2021901137 LLNL-BOOK-818513 TID-5969

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma