适应空间意识信息出租车II作为一种气味来源定位策略
Shiqi Liu1,2, Yan Zhang1,2, Shurui Fan1,2
1Innovation and Research Institute, Hebei University of Technology, Shijiazhuang 050299, China.
Entropy (Basel, Switzerland)
|April 26, 2024
概括
这项研究介绍了一种适应空间意识的Infotaxis II算法,用于增强移动机器人的嗅觉,用于危险源定位. 新方法提高了搜索效率,平衡了勘探和开采,性能优于传统策略.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 传感器系统 传感器系统
背景情况:
- 移动机器人的嗅觉对于检测安全和灾害响应中的有毒和危险物质至关重要.
- 目前的气味来源局部化策略效率低,并且可能会陷入局部最佳状态.
研究的目的:
- 提出一个适应空间意识的Infotaxis II算法,以提高移动机器人气味源定位效率.
- 为了增强机器人跟踪和探索行为,同时避免局部最佳.
主要方法:
- 开发了一个新的奖励功能,包含空间信息,并强调机器人探索.
- 实施了使用信息来调节运动范围的自适应导航更新机制.
- 使用了改进的自适应性cosine salp群算法来优化自适应性参数.
主要成果:
- 在2D和3D环境中的比较模拟表明,与经典策略相比,搜索效率更高.
- 拟议的算法在探索和利用行为之间实现了更好的平衡.
- 成功避免了过度勘探,这可能导致局部最佳.
结论:
- 适应空间意识的Infotaxis II算法显著提高了移动机器人的嗅觉,用于危险源的定位.
- 该战略提供了提高效率和平衡的方法,在复杂的环境中进行勘探和开采.
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