...
首页> 外文期刊>Robotica >Shared control methodology based on head positioning and vector fields for people with quadriplegia
【24h】

Shared control methodology based on head positioning and vector fields for people with quadriplegia

机译:基于头部定位的共享控制方法与Quadripregria人的载体字段

获取原文
获取原文并翻译 | 示例

摘要

Mobile robotic systems are used in a wide range of applications. Especially in the assistive field, they can enhance the mobility of the elderly and disable people. Modern robotic technologies have been implemented in wheelchairs to give them intelligence. Thus, by equipping wheelchairs with intelligent algorithms, controllers, and sensors, it is possible to share the wheelchair control between the user and the autonomous system. The present research proposes a methodology for intelligent wheelchairs based on head movements and vector fields. In this work, the user indicates where to go, and the system performs obstacle avoidance and planning. The focus is developing an assistive technology for people with quadriplegia that presents partial movements, such as the shoulder and neck musculature. The developed system uses shared control of velocity. It employs a depth camera to recognize obstacles in the environment and an inertial measurement unit (IMU) sensor to recognize the desired movement pattern measuring the user's head inclination. The proposed methodology computes a repulsive vector field and works to increase maneuverability and safety. Thus, global localization and mapping are unnecessary. The results were evaluated by simulated models and practical tests using a Pioneer-P3DX differential robot to show the system's applicability.
机译:移动机器人系统用于各种应用。特别是在辅助领域,他们可以增强老年人和禁用人的流动性。现代机器人技术已经在轮椅上实施,以给予他们智慧。因此,通过配备具有智能算法的轮椅,控制器和传感器,可以在用户和自主系统之间共享轮椅控制。本研究提出了一种基于头部运动和矢量字段的智能轮椅的方法。在这项工作中,用户指示在哪里进行,并且系统执行障碍物避免和规划。重点是为具有四肢瘫痪的人开发一种辅助技术,这些技术呈现出局部运动,例如肩部和颈部肌肉组织。开发系统使用共享控制速度。它采用深度摄像机来识别环境中的障碍物和惯性测量单元(IMU)传感器,以识别测量用户头部倾斜度的所需运动模式。该提出的方法计算了一种排斥矢量场,并用于提高机动性和安全性。因此,不必要的全局本地化和映射。使用Pioneer-P3DX差分机器人通过模拟模型和实际测试来评估结果,以显示系统的适用性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号