一种基于YOLO-GGCNN的机械臂检测抓取方法.pdf,本发明公开了一种基于YOLO‑GGCNN的机械臂检测抓取方法,属于智能机器人领域。所述方法利用YOLOv4深度学习网络对待抓取目标进行训练,得到训练好的模型。在机械臂抓取前,使用深度相机获取抓取平台上无抓取物体的空白深度图像
本发明公开了一种基于YOLOGGCNN的机械臂检测抓取方法,属于智能机器人领域.所述方法利用YOLOv4深度学习网络对待抓取目标进行训练,得到训练好的模型.在机械臂抓取前,使用深度相机获取抓取平台上无抓取物体的空白深度图像.放置抓取物体后,利用训练好的YOLOv4模型从RGB图像识别出待抓取目标,将识别框作为感兴趣区域,将感兴趣...
A YOLO-GGCNN based grasping framework for mobile robots in unknown environments Expert Systems with Applications Volume 225,1 September 2023, Page 119993 Purchase options CorporateFor R&D professionals working in corporate organizations. Academic and personalFor academic or personal use only. ...
In the grasping module, a two-step cascaded system, i.e., YOLOv4 and a generative grasping convolutional neural network (YOLO-GGCNN), is proposed to grasp any given object via the mobile robotic arm. The capture accuracy of our algorithm is 86.0%, and the detection time required for a ...
🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, YOLOv6, YOLOR, MODNet, YOLOX, YOLOv7, YOLOv5. MNN, NCNN, TNN, ONNXRuntime. - gg-big-org/lite.ai.toolkit