像蝙蝠一样感知:由生物仿真机制启发的层次的3D几何语义场景理解
Chi Zhang1, Zhong Yang1, Bayang Xue1
1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Biomimetics (Basel, Switzerland)
|September 27, 2023
概括
机器人现在可以理解复杂的环境,如动物使用仿生传感器和大脑启发的算法空间智能. 这种方法提高了机器人导航和未经探索的地区的场景重建能力.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 生物模拟系统 生物模拟系统
- 计算神经科学是一种神经科学.
背景情况:
- 由于传感器限制和动态环境,机器人难以理解几何语义场景.
- 人类和动物拥有先进的空间智能,对周围环境形成复杂的神经形态概念.
- 弥合动物和机器人感知之间的差距对于自主导航至关重要.
研究的目的:
- 为机器人开发一种创新的场景理解方法,灵感来自生物系统.
- 让机器人能够用几何和语义细节感知和重建尚未探索的环境.
- 为了缩小机器人和动物之间的感知差距.
主要方法:
- 提出了两种生物启发的环境感知方法:仿生传感器和由大脑启发的解析算法.
- 开发了一个系统,使机器人能够感知与蝙蝠类似的环境.
- 利用该系统进行图像语义细分和体积语义场景重建.
主要成果:
- 拟议的系统在图像语义细分方面表现出了竞争力.
- 实现了有效的体积-语义场景重建.
- 在室内环境中使用自主开发的无人机成功进行了现实世界的几何语义场景重建.
结论:
- 这种以生物为灵感的方法显著提高了机器人的几何语义场景理解能力.
- 开发的系统为机器人导航和在新的环境中重建环境提供了一个实用的解决方案.
- 这项研究为更复杂和更具适应性的机器人感知系统铺平了道路.
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