人工智能驱动的生物模拟机器人控制策略:趋势,挑战和未来方向
Hoejin Jung1, Soyoon Park1, Sunghoon Joe1
1Department of Electrical Engineering, Soongsil University, Seoul 06978, Republic of Korea.
Biomimetics (Basel, Switzerland)
|July 25, 2025
概括
人工智能通过改善控制来增强仿生机器人,使实时学习和自适应性决策成为可能. 这篇评论探讨了人工智能战略,以实现更智能,更高效的生物灵感机器人.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 生物启发工程 生物启发工程
背景情况:
- 生物仿真机器人试图复制生物系统,以提高机器人的适应能力和智能.
- 人工智能 (AI) 的整合对于推进仿生机器人控制机制至关重要.
研究的目的:
- 对仿生机器人的人工智能驱动的控制策略进行系统审查.
- 为仿生系统对人工智能的最新进展和方法进行分类.
主要方法:
- 对生物模拟机器人的关键方面 (位置,感知,认知) 的审查.
- 探索人工智能技术 (机器学习,深度学习,强化学习).
- 对各种仿生机器人应用的基于人工智能的控制方法的分析.
主要成果:
- 人工智能显著增强了控制,使实时学习和自适应性决策成为可能.
- 基于人工智能的方法显示出比传统技术更好的有效性和性能.
- 确定了针对特定仿生机器人功能量身定制的多种AI方法.
结论:
- 人工智能在推进仿生机器人技术方面发挥着关键作用.
- 未来的研究应该解决更智能和适应性更强的机器人系统面临的关键挑战.
- 人工智能集成带来更高效和更有能力的生物灵感机器人.
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