Tang Hongyan, Zhang Dan, Gan Zhongxue
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China.
Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada.
Sensors (Basel). 2020 Aug 7;20(16):4411. doi: 10.3390/s20164411.
Vertical take-off and landing unmanned aerial vehicles (VTOL UAV) are widely used in various fields because of their stable flight, easy operation, and low requirements for take-off and landing environments. To further expand the UAV's take-off and landing environment to include a non-structural complex environment, this study developed a landing gear robot for VTOL vehicles. This article mainly introduces the adaptive landing control of the landing gear robot in an unstructured environment. Based on the depth camera (TOF camera), IMU, and optical flow sensor, the control system achieves multi-sensor data fusion and uses a robotic kinematical model to achieve adaptive landing. Finally, this study verifies the feasibility and effectiveness of adaptive landing through experiments.
垂直起降无人机（VTOL UAV）因其飞行稳定、操作简便且对起降环境要求低而被广泛应用于各个领域。为了进一步将无人机的起降环境扩展到非结构化复杂环境，本研究开发了一种用于垂直起降飞行器的起落架机器人。本文主要介绍了起落架机器人在非结构化环境中的自适应着陆控制。基于深度相机（TOF相机）、惯性测量单元（IMU）和光流传感器，控制系统实现了多传感器数据融合，并使用机器人运动学模型实现自适应着陆。最后，本研究通过实验验证了自适应着陆的可行性和有效性。
