RoboCup3D 模拟环境中若干问题的研究综述

IF 2.6 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Zhongye Gao, Mengjun Yi, Ying Jin, Hanwen Zhang, Yun Hao, Ming Yin, Ziwen Cai, Furao Shen
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引用次数: 0

摘要

在机器人研究与开发过程中,由于硬件的脆弱性,通常首先使用仿真环境来验证和测试算法。RoboCup3D仿真环境基于开放式动态引擎开发,以仿人机器人NAO为主机器人模型,为仿人机器人研究人员提供了一个研究机器人动作的仿真平台。同时,它也是RoboCup 3D赛事的官方平台。在足球机器人竞赛规则下,它有助于研究多机器人,特别是多仿人机器人的合作策略。本文总结了 RoboCup3D 仿真环境的相关研究,首先介绍了该仿真环境存在的基本问题。其次,分别介绍了仿真环境中基于模型和非模型的机器人运动生成和优化研究。然后,介绍了 RoboCup3D 规则下多人形机器人合作策略设计的相关研究,包括定位、动态角色分配等。最后,分析了 RoboCup3D 仿真环境下相关研究的未来发展趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A survey of research on several problems in the RoboCup3D simulation environment

A survey of research on several problems in the RoboCup3D simulation environment

A survey of research on several problems in the RoboCup3D simulation environment

In the process of robot research and development, due to the vulnerability of hardware, simulation environment is often used to verify and test algorithms first. RoboCup3D simulation environment is developed based on open dynamic engine, and the humanoid robot NAO is modeled as the main robot, which provides a simulation platform for humanoid robot researchers to study robot movements. At the same time, it is also the official platform of RoboCup 3D events. Under the rules of soccer robot competition, it is helpful for the research of multi-robots, especially multi-humanoid robots’ cooperation strategy. This paper summarizes the related research in RoboCup3D simulation environment, and first introduces the basic problems existing in this simulation environment. Secondly, the research of robot motion generation and optimization based on model and non-model in simulation environment is introduced respectively. Then, it introduces the related research of cooperation strategy design of multi-humanoid robots under RoboCup3D rules, including positioning, dynamic role assignment, etc. And sort out a typical practical solution to the above problems; Finally, the future development trend of related research in RoboCup3D simulation environment is analyzed.

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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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