基于深度图像与三维栅格离线映射的机械臂环境建模方法
作者:
作者单位:

(1. 中国科学院沈阳自动化研究所机器人学国家重点实验室,沈阳110016;2. 中国科学院机器人与智能制造创新研究院,沈阳110016;3. 中国科学院大学,北京100049)

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通讯作者:

E-mail: zhaoyw@sia.cn.

中图分类号:

TP242

基金项目:

机器人学国家重点实验室自主课题(2017-Z09);国家自然科学基金项目(U1508208).


Environment modelling method for manipulator robot based offline-mapping between depth image and OctoMap
Author:
Affiliation:

(1. State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences, Shenyang110016,China;2. Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang110016,China;3. University of Chinese Academy of Sciences,Beijing100049,China)

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    摘要:

    为确保动态非结构化环境中人、机器人、环境3者的安全,提出一种基于深度图像与三维栅格离线映射的机械臂环境建模方法,该方法分为离线映射与在线更新两个步骤.离线映射首先将机器人工作空间划分成三维栅格,然后利用标定得到的RGB-D相机内外参数矩阵离线计算深度图像与三维栅格之间的映射关系并保存;在线更新是利用帧差法和查询离线映射表的方式更新三维栅格中的环境信息.为全面描述机器人的工作空间,进一步扩展此方法,提出多传感器信息融合以及从环境模型中滤除机械臂本体的方法.整套环境建模方法具有描述能力强、模型精度一致、可实现多传感器信息融合以及可在线更新的优点.最后,分别通过仿真实验、基于两个Kinect相机和7自由度KUKA IIWA机械臂的实际建模与末端避障实验,验证所提出方法的有效性.

    Abstract:

    In human-robot interaction process, to ensure the safety of human, robots and environment in a dynamic non-structured environment, this paper presents an environment modelling method for the manipulator robot using offline-mapping between the depth image and OctoMap. This method includes a two-stage procedure: offline mapping and online updating. In the first stage, we discretize the workspace of the robot into cells and save it as a OctoMap, then get and save the offline-mapping between pixels of depth image and cells of OctoMap using intrinsic and extrinsic matrixes of the RGB-D camera. In the second stage, the OctoMap is updated by the adjacent frame substraction and lookup to the offline-mapping. Furthermore, to fully describe the robot's workspace, data fusion of multi-RGB-D cameras and robot-body-filtering based on this mehtod are also proposed. The proposed method has the advantages of powerful description ability, consistent and high accuracy, multi-sensor data fusion ability and easily online updating. Finally, the validity of this approach is demonstrated using simulations, modelling and the obstacle avoidance experiment for the flange, which is conducted by using a 7-DOF KUKA IIWA manipulator and the Kinect sensor.

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李英立,赵忆文,王争,等.基于深度图像与三维栅格离线映射的机械臂环境建模方法[J].控制与决策,2020,35(7):1537-1546

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  • 在线发布日期: 2020-05-15
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