Naval Research Laboratory（海军研究实验室）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；University of Washington（华盛顿大学）；University of Wisconsin–La Crosse（威斯康星大学拉克罗斯分校）
David Porfirio, Laura Stegner, Maya Cakmak, Allison Sauppé, Aws Albarghouthi, Bilge Mutlu
备注：
Accepted at HRI '23, March 13-16, 2023, Stockholm, Sweden
Service robots for personal use in the home and the workplace require end-user development solutions for swiftly scripting robot tasks as the need arises. Many existing solutions preserve ease, efficiency, and convenience through simple programming interfaces or by restricting task complexity. Others facilitate meticulous task design but often do so at the expense of simplicity and efficiency. There is a need for robot programming solutions that reconcile the complexity of robotics with the on-the-fly goals of end-user development. In response to this need, we present a novel, multimodal, and on-the-fly development system, Tabula. Inspired by a formative design study with a prototype, Tabula leverages a combination of spoken language for specifying the core of a robot task and sketching for contextualizing the core. The result is that developers can script partial, sloppy versions of robot programs to be completed and refined by a program synthesizer. Lastly, we demonstrate our anticipated use cases of Tabula via a set of application scenarios.
Language and Sketching: An LLM-driven Interactive Multimodal Multitask Robot Navigation Framework
ShanghaiTech University（上海科技大学）；Harbin Institute of Technology（哈尔滨工业大学）；University of Shanghai for Science and Technology（上海理工大学）；The University of Manchester（曼彻斯特大学）；University College London（伦敦大学学院）
On-the-fly hand-eye calibration for the da Vinci surgical robot
Department of Mechanical Engineering, Imperial College London（帝国理工学院机械工程系）；Mechatronics in Medicine Laboratory（医学机电实验室）；Hamlyn Centre for Robotics Surgery（机器人外科哈姆林中心）
Design and Simulation of an Autonomous Quantum Flying Robot Vehicle: An IBM Quantum Experience
Indian Institute of Science Education and Research, Berhampur（贝兰布尔印度科学教育与研究学院）；National Institute of Science Education and Research, HBNI（霍米·巴巴国家研究所国家科学教育与研究学院）；Bikash’s Quantum (OPC) Pvt. Ltd.（比卡什量子私人有限公司）
Why Evolve When You Can Adapt? Post-Evolution Adaptation of Genetic Memory for On-the-Fly Control
School of Engineering and Physical Sciences, Heriot-Watt University Dubai（工程与物理科学学院，惠顿大学迪拜分校）；School of Mathematical and Computer Sciences, Heriot-Watt University Dubai（数学与计算机科学学院，惠顿大学迪拜分校）
On-the-Fly VLA Adaptation via Test-Time Reinforcement Learning
University of Missouri–Kansas City（密苏里大学堪萨斯城分校）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；U. S. Naval Research Laboratory（美国海军研究实验室）；Lamar University（拉马尔大学）；Meta AI；Rochester Institute of Technology（罗彻斯特理工学院）
Learning to Fly via Deep Model-Based Reinforcement Learning
Volkswagen Group, Machine Learning Research Lab（大众集团机器学习研究实验室）；Technical University of Darmstadt（达姆施塔特工业大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
Deployment of Aerial Robots after a major fire of an industrial hall with hazardous substances, a report
University of Applied Science, Gelsenkirchen（盖尔森基兴应用科学大学）；German Rescue Robotic Centre, Dortmund（多特蒙德德国救援机器人中心）；Fire Department of Dortmund, Institute of Fire Service and Rescue Technology（多特蒙德消防局消防与救援技术研究所）
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback
Seoul National University（首尔国立大学）；Carnegie Mellon University（卡内基梅隆大学）；University of Maryland, College Park（马里兰大学帕克分校）；All Purpose AI；Kyung Hee University（庆熙大学）
