Robotics Notes
LINK === https://tinurll.com/2tD9XN
Moving on to the next stage of his plans, Kimijima deletes Airi and seizes control of Akiho's older sister Misaki, stealing an experimental battle robot called SUMERAGI and destroying the Gunbuild-2. Meanwhile, the Committee of 300 orchestrates mass robot rebellions all over Japan, plunging the country into chaos while a commando team seizes the Tanegashima Space Center with the help of SUMERAGI. The robotics club is then approached by Nae Tennouji and Toshiyuki Sawada, who reveal they are part of a secret group that resists against the Committee of 300, and that the Committee plans to use Tanegashima to launch a rocket containing bombs that will create a apocalyptic solar flare that will wipe out the majority of humanity, allowing the Committee to rule over the survivors and rebuild the world according to their will. Sawara provides the robotics club with a special code that can completely delete Kimijima, but requires them to be in close range to send it. Working together with the other Tanegashima residents, the robotics club upgrades Gunbuild-1 into the Super Gunbuild-1 and Kaito pilots it against SUMERAGI while Nae neutralizes the commandos. Kaito is able to force Misaki to exit her cockpit, leaving Kimijima vulnerable and allowing Kaito to delete him, though Kimijima boasts that another copy of himself will surely surface.
What probably makes this all the more painful is that Robotics;Notes, when it gets going, has a lovely laidback pacing to it, that while it won't appeal to everyone - certainly feels appropriate for the type of more interpersonal story between the cast of the Central T. Robot Club. Instead of earth-shattering conspiracies, most of what the story tackles during its runtime is decidedly smaller in scale. Junna, a girl struggling with self-confidence and anxiety; Subaru, a boy caught between his Father's expectation for him to take over his fishing job, and his own passion for robotics; Frau, a girl that has forsaken human communication all in the effort of finding her lost mother, struggling to learn to communicate face-to-face again and get out of her shell. There's more to each of these character's stories than meets the eye, and some of them do grow considerably in scope for their respective chapters, but the point remains - almost ironically for a story so focused on robots, Robotics;Notes really emphasizes its heart with its much more down-to-earth tale.
Robotics;Notes tells the story of Kaito, a senior at Tanegashima High. While he is unamused with life and only interested in playing video games, his best friend Akiho Senomiya has big dreams and an even bigger legacy to live up to. Her now-famous sister started the robotics club at the school and began working on building a life-size Gundam based on Gunvarrel, a mecha in a popular anime. Kaito unwittingly tags along as Akiho works to build the robot, reconnect with her older sister, and gather new members for the club. However, he soon stumbles upon a mysterious document that could spell doom for humanity as they know it if he does not unravel the truth in time.
The background art of the game is also quite breathtaking. Unlike most of the other games in the series, which take place in Shibuya and Akihabara, crowded city locations, the island of Tanegashima feels fresh and inviting. The art does a fantastic job at selling the relatively rural community as a wonderful place for tourists to visit, and the vibrant color palette contrasts these nicely against scenes that take place inside locations like the robotics club hangar.
The PDF version of these notes are autogenerated from the HTML version. There are a few conversion/formatting artifacts that are easy to fix (please feel free to point them out). But there are also interactive elements in the HTML version are not easy to put into the PDF. When possible, I try to provide a link. But I consider the online HTML version to be the main version.
This book is about nonlinear dynamics and control, with a focus on mechanical systems. I've spent my career thinking about how to make robots move robustly, but also with speed, efficiency, and grace. I believe that this is best achieved through a tight coupling between mechanical design, passive dynamics, and nonlinear control synthesis. These notes contain selected material from dynamical systems theory, as well as linear and nonlinear control. But the dynamics of our robots quickly get too complex for us to handle with a pencil-and-paper approach. As a result, the primary focus of these notes is on computational approaches to control design, especially using optimization and machine learning. When I started teaching this class, and writing these notes, the computational approach to control was far from mainstream in robotics. I had just finished my Ph.D. focused on reinforcement learning (applied to a bipedal robot), and was working on optimization-based motion planning. I remember sitting at a robotics conference dinner as a young faculty, surrounded by people I admired, talking about optimization. One of the senior faculty said \"Russ: the people that talk like you aren't the people that get real robots to work.\" Wow, have things changed. Now almost every advanced robot is using optimization or learning in the planning/control system.
Although the material in the book comes from many sources, the presentation is targeted very specifically at a handful of robotics problems. Concepts are introduced only when and if they can help progress the capabilities we are trying to develop. Many of the disciplines that I am drawing from are traditionally very rigorous, to the point where the basic ideas can be hard to penetrate for someone that is new to the field. I've made a conscious effort in these notes to keep a very informal, conversational tone even when introducing these rigorous topics, and to reference the most powerful theorems but only to prove them when that proof would add particular insights without distracting from the mainstream presentation. I hope that the result is a broad but reasonably self-contained and readable manuscript that will be of use to any enthusiastic roboticist.
The material in these notes is organized into a few main parts. \"Model Systems\" introduces a series of increasingly complex dynamical systems and overviews some of the relevant results from the literature for each system. \"Nonlinear Planning and Control\" introduces quite general computational algorithms for reasoning about those dynamical systems, with optimization theory playing a central role. Many of these algorithms treat the dynamical system as known and deterministic until the last chapters in this part which introduce stochasticity and robustness. \"Estimation and Learning\" follows this up with techniques from statistics and machine learning which capitalize on this viewpoint to introduce additional algorithms which can operate with less assumptions on knowing the model or having perfect sensors. The book closes with an \"Appendix\" that provides slightly more introduction (and references) for the main topics used in the course. 781b155fdc