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

基本信息

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

项目摘要

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化，感知能力太差，太不合作，太不安全，无法大规模生产。为了提高社会关怀、制造、物流、服务、检验或农业等具有战略意义的领域的生产力，下一代机器人需要能够以迄今为止前所未有的敏锐度来感知、解释、行动、导航、协调和协作。愿景：该研究计划的总体目标是提供增强人类能力和潜力的自主系统。这些机器人必须能够有效地执行各种定制任务，并且需要最少的操作员干预。在可持续发展的国家卓越中心，我们将发展强大的体现智能的技术和人员基础，即使机器人能够在现实世界中稳健而灵活地行动、互动和协作的科学和技术。战略：我们的重点是工程、探索和利用集成体现智能的构建模块，以提供自主系统，这些系统在其整个生命周期中获得感知、感知、操纵、导航、协作和解决问题所需的能力使他们能够独立运作，同时显着提高人类生产力。我们将通过利用跨研究学科的协同效应，显着扩大机器人在战略和商业价值领域的覆盖范围和多功能性，这种协同效应只有在部署机器人系统时才会出现。在此过程中，我们受到基础科学问题和现实应用的驱动。我们与合作伙伴一起制定了明确的目标：多功能的协作机器人，其社会和经济影响力巨大。我们的工作将通过仔细考虑和连贯的研究计划来支持国家战略目标：从传感到协作。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Bayesian reinforcement learning for single-episode missions in partially unknown environments

部分未知环境中单集任务的贝叶斯强化学习

DOI：
发表时间：
2022
期刊：
影响因子：
0
作者：
Budd M
通讯作者：
Budd M

Risk-Aware Motion Planning in Partially Known Environments

部分已知环境中的风险感知运动规划

DOI：
http://dx.10.48550/arxiv.2109.11287
发表时间：
2021
期刊：
影响因子：
0
作者：
Barbosa F
通讯作者：
Barbosa F

What Goes Around: Leveraging a Constant-Curvature Motion Constraint in Radar Odometry

发生了什么：在雷达里程计中利用恒定曲率运动约束

DOI：
http://dx.10.1109/lra.2022.3186757
发表时间：
2022
期刊：
IEEE Robotics and Automation Letters
影响因子：
5.2
作者：
Aldera R
通讯作者：
Aldera R

Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks

从智能水下传感器网络收集 AUV 数据的概率规划

DOI：
10.1109/iros47612.2022.9981460
发表时间：
2022-10-23
期刊：
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
影响因子：
0
作者：
Matthew Budd;G. Salavasidis;Izzat Karnarudzaman;C. Harris;A. Phillips;Paul Duckworth;Nick Hawes;Bruno Lacerda
通讯作者：
Bruno Lacerda

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