Developmental algorithms for robotics: Understanding the world of objects, interactions and tools.

机器人技术的开发算法：理解对象、交互和工具的世界。

• 批准号: EP/M013510/1
• 负责人: Qiang Shen
• 金额: $ 71.24万
• 依托单位: Aberystwyth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FM013510%2F1
• 关键词: Developmental; algorithms; robotics; Understanding; world

This research project is a psychologically-inspired investigation of an analogy of infant play as the central mechanism for autonomous, self-motivated robots that learn the local physics of their world.We note that infants and children at play exhibit exactly the kind of autonomous learning that would be very desirable in robotics. Infant play has a major role in the acquisition of new skills and cognitive growth. Noticing that early infants spend hours in play, we have designed a computer analogy of infant play and this project is an in-depth investigation into the use of play as a means of building subjective understanding of the physics of the local world.The project will implement a play generator algorithm on an iCub humanoid robot and perform experiments with a wide range of scenarios involving varieties of objects. This includes playing solitarily with objects to learn their properties, and interactive play with a human participant. We also include experiments with tool use (using one object as a tool for acting on another) to investigate how objects may become extensions of self.A panel of selected scientific experts on infants and play will provide their psychological expertise throughout the project and will also assist with the design of a series of matching experiments that will compare results from the robot model with those from selected psychological experiments on infants.The data from the experiments will be analysed and interpreted to shed light on a set of scientific issues. When we report on the results we will also extract some general principles for robot learning through play. We will examine the applicability of these principles in new robotic and intelligent systems developments. For example, we anticipate particular applications in areas such as assistive technology and home care where the re-programming of mass-produced systems is not feasible. We believe technology with a developmental approach will have wide implications and provide an alternative to "building robots" by establishing the idea of "developing robots" for applications.

这个研究项目是一个受心理学启发的研究，将婴儿玩耍比作自主的、自我激励的机器人学习其世界的局部物理的中心机制。我们注意到，玩耍的婴儿和儿童表现出的正是机器人学中非常理想的自主学习。婴儿游戏在获得新技能和认知发展方面发挥着重要作用。注意到早期的婴儿在游戏中花费数小时，我们设计了一个婴儿游戏的计算机模拟，这个项目是一个深入的研究，使用游戏作为建立对当地世界物理的主观理解的手段。该项目将在iCub人形机器人上实现游戏生成器算法，并在涉及各种物体的广泛场景下进行实验。这包括独自玩物体以学习它们的属性，以及与人类参与者进行交互式游戏。我们还包括使用工具的实验（将一个物体作为作用于另一个物体的工具）一个由婴儿和玩耍方面的科学专家组成的小组将在整个项目中提供他们的心理学专业知识，并将协助设计一系列匹配实验，将机器人模型的结果与选定的心理学实验的结果进行比较。将对实验数据进行分析和解释，以阐明一系列科学问题。当我们报告结果时，我们还将提取一些通过游戏进行机器人学习的一般原则。我们将研究这些原则在新的机器人和智能系统开发中的适用性。例如，我们预计在辅助技术和家庭护理等领域的特定应用，其中大规模生产的系统的重新编程是不可行的。我们相信，具有开发方法的技术将产生广泛的影响，并通过建立“开发机器人”应用的想法来提供“建造机器人”的替代方案。

项目成果

Robot Multimodal Object Perception and Recognition: Synthetic Maturation of Sensorimotor Learning in Embodied Systems

• DOI: 10.1109/tcds.2020.2965985
• 发表时间: 2021-06-01
• 期刊: IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
• 影响因子: 5
• 作者: Braud，Raphael;Giagkos，Alexandros;Shen，Qiang
• 通讯作者: Shen，Qiang

How to Grow a Robot - Developing Human-Friendly, Social AI

如何培育机器人 - 开发人性化的社交人工智能

• DOI: 10.7551/mitpress/12511.001.0001
• 发表时间: 2020
• 作者: Lee M

Discovering Schema-Based Action Sequences Through Play in Situated Humanoid Robots

• DOI: 10.1109/tcds.2021.3094513
• 发表时间: 2022-09-01
• 期刊: IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
• 影响因子: 5
• 作者: Kumar，Suresh;Giagkos，Alexandros;Shen，Qiang
• 通讯作者: Shen，Qiang

Assessing Humanoid Multimodal Grasping Towards Object Recognition

评估面向对象识别的人形多模式抓取

• 发表时间: 2017
• 作者: Alexandros Giagkos

Developing Hierarchical Schemas and Building Schema Chains Through Practice Play Behavior.

• DOI: 10.3389/fnbot.2018.00033
• 发表时间: 2018
• 期刊: Frontiers in neurorobotics
• 影响因子: 3.1
• 作者: Kumar S;Shaw P;Giagkos A;Braud R;Lee M;Shen Q
• 通讯作者: Shen Q