DroneTrap: 由有色力探测和手势识别的软机器人手在米达里捕捉无人机 (DroneTrap: Drone Catching in Midair by Soft Robotic Hand with Color-Based Force Detection and Hand Gesture Recognition)

Aleksey Fedoseev,Valerii Serpiva,Ekaterina Karmanova,Miguel Altamirano Cabrera,Vladimir Shirokun,Iakov Vasilev,Stanislav Savushkin,Dzmitry Tsetserukou

from arxiv, Accepted to the 4th IEEE International Conference on Soft Robotics (RoboSoft), IEEE copyright, "(c) 20XX IEEE...", 7 pages, 15 figures

The paper proposes a novel concept of docking drones to make this process as safe and fast as possible. The idea behind the project is that a robot with the gripper grasps the drone in midair. The human operator navigates the robotic arm with the ML-based gesture recognition interface. The 3-finger robot hand with soft fingers and integrated touch-sensors is pneumatically actuated. This allows achieving safety while catching to not destroying the drone's mechanical structure, fragile propellers, and motors. Additionally, the soft hand has a unique technology of providing force information through the color of the fingers to the remote computer vision (CV) system. In this case, not only the control system can understand the force applied but also the human operator. The operator has full control of robot motion and task execution without additional programming by wearing a mocap glove with gesture recognition, which was developed and applied for the high-level control of DroneTrap. The experimental results revealed that the developed color-based force estimation can be applied for rigid object capturing with high precision (95.3\%). The proposed technology can potentially revolutionize the landing and deployment of drones for parcel delivery on uneven ground, structure inspections, risque operations, etc.

翻译：本文提出了一个关于对无人机进行对接的新概念,以使这一过程尽可能安全和快速。项目背后的理念是,一个手持牵引器的机器人在空中捕捉无人机。人操作员通过ML的动作识别界面对机器人臂进行导航。三指机器人手用软手指和综合触摸传感器进行气动活化。这样就可以在捕捉不摧毁无人机的机械结构、脆弱推进器和发动机的同时实现安全。此外,软手有一个独特的技术,通过远程计算机视觉系统的手指颜色提供武力信息。在这种情况下,不仅控制系统能够理解所应用的武力,而且还能够理解人类操作者。操作员完全控制机器人运动和任务执行,而无需额外编程,同时佩戴带有手势识别的毛帽手套进行额外的编程。这是为高水平控制DrooneTrap开发和应用的。实验结果表明,开发的基于颜色的力量估计可用于高精确度的硬性物体捕捉取(95.3 ⁇ )。拟议的技术可以使地面投送的无人机的着陆和部署结构发生革命。