基于强化学习的框架,通过自主传感机器人进行鱼聚会
Ninad Jadhav1,2, Sushmita Bhattacharya1,2, Daniel Vogt1,2
1Project CETI, New York, NY, USA.
Science robotics
|October 30, 2024
概括
研究人员开发了一个人工智能框架,用于自主机器人与精油见面,克服鱼潜水模式带来的挑战. 该系统通过改进机器人导航和跟踪能力来增强生物观测机会.
科学领域:
- 机器人学和海洋生物学
- 人工智能和信号处理
背景情况:
- 长时间的潜水模式挑战了生物观测的努力.
- 对于与野生动物相遇的自主机器人导航,需要强大的跟踪和约会策略.
研究的目的:
- 开发一种算法框架,以最大限度地利用自主机器人与鱼相遇的机会.
- 整合用于机器人路由和基于VHF信号的轴承估计的多代理强化学习,用于鱼跟踪.
主要方法:
- 提出了一个框架,结合了基于强化学习的自主模块和基于合成光圈雷达的VHF信号传感模块.
- 该系统利用噪音轴承测量,鱼发声,VHF标签和潜水行为进行导航.
- 现场实验使用了"工程鱼" (带有VHF标签的快艇) 和未标记的鱼的仅声学跟踪.
主要成果:
- 传感模块在VHF标签上实现了10.55°的中位轴承误差.
- 自主模块使用三台机器人证明了81.31%的会成功率与500米的工程鱼在500米使用三个机器人.
- 通过使用两个机器人,在1000米处的未标记的精油中实现了68.68%的约会成功率.
结论:
- 拟议的算法框架有效地提高了自主机器人与精油的约会能力.
- 该系统通过实现可靠的跟踪和接近,有望改善生物观测.
- 通过真实实验和数据集的验证证实了算法的实际适用性.
相关概念视频
01:12Observational Learning
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...
01:23Reinforcement
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Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example: