加州理工学院的自主系统与技术研究中心(Center for Autonomous Systems and Technologies,简称CAST)是一个先进的研究机构,致力于推动自主系统在各种环境中的研发,该中心集合了机器人学、无人驾驶车辆、无人机技术、及人工智能领域的专家,共同探索、创新,推动自主技术的边界。
CAST拥有一个名为Aerodrome的无人机测试室,允许研究人员在受控环境中进行实验和测试,此外,CAST还拥有高级机器人实验室和自主系统研发设备,这为从机器学习算法的开发到硬件集成提供了全方位的支持。
研究领域与项目:
1. 自动化交通工具:这个领域集中在自主驾驶的多个方面,包括传感技术、决策算法和人机交互,目标不仅是让车辆自主行驶,还要确保其与人及其他交通工具的安全交互,此外,也研究无人机的导航与控制技术,特别是在复杂的都市环境中。
2. 机器人互动:这个领域致力于解决机器人与人、环境和其他机器人互动的挑战,研究的核心是确保机器人理解人类的指示,并在不同的环境中做出适当的响应,项目还探讨了多机器人协同作业和团队工作的概念。
3. 自主决策:在这个领域,研究人员研究如何使机器在不确定和动态环境中做出决策,这包括利用深度学习和强化学习技术来培训机器在复杂场景中自行决策。
4. 人工智能算法:此领域旨在开发新的计算方法,以使机器能够理解、学习和适应复杂环境,研究人员在此领域中使用神经网络和其他机器学习技术,使机器人和自动驾驶车辆能够更好地理解其所处的环境和进行实时决策。
CAST不仅在技术领域取得了突破,而且它的研究成果已经被广泛应用于现实生活中,从增强无人驾驶车辆的安全性到为复杂的手术提供机器人助手,其在人工智能和自主系统领域的开创性工作也为全球的科研机构和企业提供了宝贵的资源和启示。
The Center for Autonomous Systems and Technologies (CAST) at the California Institute of Technology (Caltech) stands as a beacon of advanced research dedicated to pushing the boundaries of autonomous systems across various environments. Drawing together experts from robotics, driverless vehicles, drone technology, and artificial intelligence, CAST fosters an environment of exploration and innovation in the domain of autonomy.
Central to CAST's infrastructure is the Aerodrome, a specialized lab for drone testing, permitting researchers to conduct experiments in a controlled setting. Further, CAST boasts advanced robotic laboratories and infrastructure for the development of autonomous systems, offering an all-encompassing platform that spans from the development of machine learning algorithms to hardware integration.
Research Domains & Projects:
1. Automated Transport: This domain hones in on various facets of autonomous driving, encompassing sensor technologies, decision-making algorithms, and human-machine interaction. The goal stretches beyond merely enabling vehicles to drive autonomously but to ensure their safe interaction with humans and other modes of transportation. Moreover, navigation and control technologies for drones, especially in intricate urban environments, are explored.
2. Robotic Interaction: Dedicated to tackling challenges inherent in robot interactions with humans, the environment, and other robots, the core of this domain ensures that robots understand directives from humans and respond aptly across different environments. The realm also delves into concepts of multi-robot collaborative operations and teamwork.
3. Autonomous Decision-making: Researchers in this domain delve into enabling machines to make decisions in uncertain and dynamic scenarios. This encompasses leveraging deep learning and reinforcement learning techniques to train machines to act autonomously in complex settings.
4. AI Algorithms: Aimed at crafting new computational methods to empower machines to understand, learn, and adapt to intricate environments, researchers harness neural networks and other machine learning techniques to equip robots and autonomous vehicles with better real-time decision-making capacities in their respective environments.
CAST's strides are not limited to technical breakthroughs alone. Its research outcomes have found practical applications that range from enhancing the safety of autonomous vehicles to providing robotic assistants for intricate surgeries. The trailblazing work in artificial intelligence and autonomous systems also serves as invaluable resources and insights for global research institutions and industries.