在自动驾驶汽车中集成MoS2同晶体管设备和用于传感器融合的模拟电路,以定位目标
Tian Tan1, Haoyue Guo2, Yida Li2
1School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
ACS nano
|May 16, 2024
概括
研究人员开发了一种模拟卡尔曼波器,使用二硫化晶体管来实现更快,更节能的自动驾驶传感器融合. 这种新的方法加快了处理速度,提高了本地化准确性,克服了数字电路的局限性.
科学领域:
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
- 机器人技术 机器人技术 机器人技术
背景情况:
- 自动驾驶中的传统数字处理器由于模拟到数字转换和向量矩阵操作而面临能源和速度限制.
- 在自动驾驶汽车中精确定位的传感器融合需要高效和快速的数据处理.
研究的目的:
- 为了呈现一个模拟的卡尔曼波器电路使用二硫化物 (MoS2) memtransistors.
- 为了加速传感器融合,在自动驾驶汽车应用中实现精确定位.
主要方法:
- 开发了一个基于MoS2记忆晶体管的模拟卡尔曼过电路.
- 杆式memtransistor非挥发性内存用于存储卡尔曼增益,消除了数据的融合.
- 利用导电状态的门终端调制,以获得可适应的卡尔曼波器收益.
主要成果:
- 通过消除数据收,实现了加速处理速度.
- 通过融合LiDAR,雷达和摄像头数据,证明了对车辆位置坐标的准确估计.
- 展示了在无信号交叉路口中成功解决现实世界的问题.
- 与数字电路相比,报告了能源效率的1000倍提高.
结论:
- 在先进的传感器融合中,MoS2晶体管对快速,节能实时传感和连续信号处理具有可行性.
- 拟议的模拟卡尔曼波器电路提高了自动驾驶本地化准确性和效率.
相关概念视频
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