From Sensing to Collaboration: Engineering, Exploring and Exploiting the Building Blocks of Embodied Intelligence - An EPSRC Programme Grant

从感知到协作：工程、探索和利用体现智能的构建模块 - EPSRC 计划资助

• 批准号: EP/V000748/1
• 负责人: Ingmar Posner
• 金额: $ 763.83万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV000748%2F1
• 关键词: Sensing; Collaboration; Engineering; Exploring; Exploiting

Our robots are too specialised, too impoverished in their sensing, too uncooperative and too unsafe to be productive at scale. To contribute to productivity in strategically important areas such as social care, manufacturing, logistics, service, inspection or agriculture, future generations of robots need to be able to sense, interpret, act, navigate, coordinate and collaborate with an hitherto unprecedented acuity. VISION: The overarching aim of this research programme is to deliver autonomous systems which amplify human capacity and potential. These robots must be capable of performing a broad array of bespoke tasks effectively, and with a minimum of operator intervention. In a sustainable national centre of excellence we will grow the technology and people substrate for robust embodied intelligence, i.e. the science and technology to enable robots to robustly and flexibly act, interact and collaborate in the real world. STRATEGY: Our focus is on engineering, exploring and exploiting the building blocks of integrated embodied intelligence to deliver autonomous systems which, over the course of their life-time, acquire the sensing, perception, manipulation, navigation, collaboration and problem solving abilities required to allow them to operate unaided while significantly enhancing human productivity. We will significantly expand the reach and versatility of robots in domains of strategic and commercial value by exploiting synergies across research disciplines, which only emerge when deploying robot systems. In doing so we are driven by both fundamental science questions and real-world applications. Together with our partners, we have a clear scope in mind: versatile, collaborative robots whose societal and economic footprint is vast. Our work will underpin a national strategic aim with a carefully considered and coherent programme of research: from sensing to collaboration.

我们的机器人太专业了，感应太贫穷，太不合作了，太不安全了，无法在大规模上发挥作用。为了在战略上重要领域（例如社会护理，制造业，服务，检查或农业）促进生产力，未来的机器人需要能够感知，解释，采取行动，导航，协调，协调和协作，并与迄今为止前所未有的敏锐度合作。愿景：该研究计划的总体目的是提供扩大人类能力和潜力的自治系统。这些机器人必须能够有效地执行广泛的定制任务，并且最少的操作员干预。在一个可持续的国家卓越中心，我们将发展技术和人的基础，以实现强大的体现情报，即科学和技术，使机器人能够在现实世界中稳健，灵活地行动，互动和协作。策略：我们的重点是工程，探索和利用综合体现智能的组成部分，以提供自主系统，这些系统在其一生的过程中，获得感应，感知，操纵，导航，协作和解决问题的能力，使它们能够无助于他们，同时可以显着提高人类生产力。我们将通过利用跨研究学科的协同作用来大大扩展机器人在战略和商业价值领域的覆盖范围和多功能性，这仅在部署机器人系统时出现。这样一来，我们都受到基本科学问题和现实世界应用的驱动。与我们的合作伙伴一起，我们有一个清晰的范围：多功能，合作的机器人，其社会和经济足迹很大。我们的工作将以精心考虑的研究计划：从感知到协作，以实现国家战略目标。

项目成果

RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning

RAMP：评估机器人装配操作和规划的基准

• DOI: 10.1109/lra.2023.3330611
• 发表时间: 2023
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Collins J

A Local Filtering Technique for Robot Skin Data

• DOI: 10.1109/lra.2021.3098457
• 发表时间: 2021-10
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: A. Albini;G. Cannata;P. Maiolino

Time-bounded large-scale mission planning under uncertainty for UV disinfection

紫外线消毒不确定性下有时间限制的大规模任务规划

• 发表时间: 2022
• 作者: Brudermüller L

Beta residuals: improving fault-tolerant control for sensory faults via bayesian inference and precision learning

Beta 残差：通过贝叶斯推理和精度学习改进感知故障的容错控制

• 发表时间: 2022
• 期刊: IFAC-PapersOnLine, 55(6), 285-291
• 作者: Baioumy M

Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks

• DOI: 10.1109/iros47612.2022.9981460
• 发表时间: 2022-10
• 期刊: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 作者: Matthew Budd;G. Salavasidis;Izzat Karnarudzaman;C. Harris;A. Phillips;Paul Duckworth;Nick Hawes;Bruno Lacerda