麻豆视频

听补苍诲听

The Targeted Observation by Radars and UAS of Supercells (TORUS) projects are conducted by more than 50 scientists and students deploying a broad suite of cutting-edge instrumentation into the US Great Plains during the 2019 and 2023聽storm seasons.听TORUS aims to use the data collected to improve the conceptual model of supercell thunderstorms (the parent storms of the most destructive tornadoes) by exposing how small-scale structures within these storms might lead to tornado formation.

ALPACA: Autonomous Learning with Probability & Abstraction for Competency Awareness

This project developed ALPACA (Autonomous Learning with Probability & Abstraction for Competency Awareness), a general framework for competency-aware autonomous agents, particularly those based on reinforcement learning (RL). ALPACA provides insight into RL agent competencies and empowers users to examine and constrain agent behavior, facilitating trust building with human teammates and dramatically improving safety for real-world applications.

Multi-vehicle Collaboration with Minimal Communications and Minimal Energy

This project developed a hierarchical autonomous mission planning and response capability for Autonomous Underwater Vehicles (AUVs) to address the challenges associated with long duration operations. The research is innovating approaches to the exchange of information between collaborating vehicles enabling onboard decision-making to perform effectively despite communication limitations imposed by the underwater maritime environment.

The DARPA Subterranean, or "SubT", Challenge seeks novel approaches to rapidly map, navigate, and search underground environments during time-sensitive combat operations or disaster response scenarios. As a response to the challenge, MARBLE is a small team of autonomous robotic drones (ground, legged, and aerial) equipped to deploy a temporary, highly adaptable wireless mesh network and use it to simultaneously map, navigate and search the underground environment鈥檚 tunnels, identify artifacts and communicate information to an above-ground relay station.

Targeted observation and seeding using autonomous unmanned aircraft systems

The main goal of this research is to develop and assess an autonomous UAS that utilizes in-situ real time data to sense, target and implement seeding.听This project addresses an innovative approach towards autonomous enhancement of precipitation: to develop new sensing technologies, to create new data assimilation tools, to design novel targeted sampling and delivery strategies, and to integrate them into an unmanned aircraft system (UAS) for real-time, autonomous guidance of rainfall enhancement operations.

I/UCRC Phase 2: Center for Unmanned Aircraft Systems: I/UCRC for Unmanned Aircraft Systems

The Center for Unmanned Aircraft Systems (C-UAS) was established in 2012 and is an聽Industry/University Cooperative Research Center聽involving Brigham Young University,聽the University of Colorado at Boulder,聽Virginia Tech,聽the University of Michigan, and Texas A&M University.听The center is the only National Science Foundation-funded unmanned aircraft research center.

Coordinated Persistent Airborne Information Gathering: Cloud Robotics in the Clouds

This project聽investigated coordinated energy-aware information-gathering by dynamic, data-driven reasoning across four inter-related layers: the sensing layer that focuses on information-theoretic formulations of mission tasks; the communication layer that learns models of networked communication behavior for improved coordination in denied or stressed environments; the environment layer whereby the dynamics of the atmosphere drive aircraft performance; and the platform layer where sensors embedded into the UAS platform provide novel flight performance data.

Severe-storm Targeted Observation and Robotic Monitoring (STORM)

This project addresses the development of autonomous self-deploying aerial robotic systems (SDARS) that will enable new in-situ atmospheric science applications through targeted observation.

User-Adaptive Assurances for Enhancing Trust

This project will investigate the closed loop interactions between assured autonomy and user trust.听This project investigates a model-based approach to understanding how user trust evolves in systems consisting of a supervising user and an autonomous agent.

Scalable Cooperative Tracking of Moving RF Ground Targets

This work will develop a new approach to decentralized sensor fusion and trajectory optimization to enable multiple networked UAS assets to cooperatively localize moving RF signal sources on the ground in the presence of uncertainties in ownship states and sensing models. Our approach ties together model predictive planning with the recently developed idea of factorized distributed data fusion, which allows each tracker vehicle to ignore state uncertainties for other vehicles and absorb new target state and local model information without sacrificing overall estimation performance.听

Project Storm

Project Storm leverages the CU-Boulder鈥檚 proven expertise and extensive capability in nomadic, integrated collection of real-time supercell data using unmanned aircraft systems (UAS) to better predict tornadogenesis and dramatically increase Tornado Warning lead-time.听 CU-Boulder collaborates with an established network of government, academic, and industry partners to improve measurement and collection of supercell data.听 The CU-Boulder Earth Lab works closely with IRISS to process and distribute datasets for improved tornado forecasting techniques.

Project Forest

Project Forest will employ CU-Boulder鈥檚 highly sophisticated unmanned aircraft infrastructure for remote sensing, data collection, and monitoring of ecosystem health -聽such as vegetation growth and tree distribution.听 Earth Lab will then process and analyze collected data in collaboration with the Cooperative Institute for Research in Environmental Sciences (CIRES) and the Institute of Arctic and Alpine Research (INSTAAR), also located in Boulder, to inform future ecological and conservationist endeavors.

Persistent Information-Gathering with Airborne Surveillance and Communication Networks in Fading Environments

The purpose of this collaborative effort is to develop and evaluate a hierarchical framework for real-time, path planning for persistent information-gathering tasks in fading communication environments. Novel features of the proposed work are learning the radio environment and background winds; consideration of the energy that can be gained from wind field patterns (energetics); and a persistent, communication-aware information-based formulation of sensing tasks (informatics) that can integrate multiple sensing modalities.

Collaborative Research: IUCRC: FRP: Network Enabled Airborne Autonomy

This effort will investigate the value of utilizing cloud robotics techniques for network-enabled airborne autonomy. Algorithms will be designed and assessed that allow cooperating unmanned aircraft to access dispersed cloud computing resources. This infrastructure will be used to perform complex computation in support of autonomous perception, planning, and learning tasks.

Funded by the National Science Foundation (NSF), the goal of this project is to聽further the knowledge of the nature of elevated convection with heavy rain. The University of Colorado is teaming with the University of Missouri and the University of Nebraska to integrate unmanned aircraft into the PRECIP field campaign.

Efficient Reconfigurable Cockpit Design and Fleet Operations using Software Intensive, Networked and Wireless Enabled Architecture (ECON)

The purpose of this project is to investigate the utility of software-intensive, networked, wireless, reconfigurable cockpit design for safe and efficient fleet operations. A large collaborative team is being led by the NASA Ames Research Center. We will make specific contributions in the area of cybersecurity for networked operations.