Zhao Xu, Dou Lihua, Su Zhong, Liu Ning
School of Automation, Beijing Institute of Technology, Beijing 100081, China.
Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science & Technological University, Beijing 100101, China.
Sensors (Basel). 2018 Mar 16;18(3):879. doi: 10.3390/s18030879.
A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot's motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot's motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot's navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots.
蛇形机器人是一种高度冗余的移动机器人,与履带式机器人、轮式机器人和腿式机器人有显著区别。为了解决蛇形机器人在无辅助定位的应用环境中进行自定位的问题,提出了一种基于蛇形机器人运动特性约束的自主导航方法。该方法利用蛇形机器人自身的微机电系统(MEMS)惯性测量单元(IMU),实现了无节点且无外部辅助的蛇形机器人的自主导航。首先,研究蛇形机器人的运动特性,建立运动学模型,然后分析运动约束特性和运动误差传播特性。其次,探索蛇形机器人的导航布局,提出约束准则和固定关系,并根据蛇形机器人的运动特征和控制模式进行零状态约束。最后,在其运动特性约束下,基于扩展卡尔曼滤波器(EKF)位置估计方法实现自主导航定位。通过自主研发的蛇形机器人进行测试,验证了所提方法的有效性,位置误差小于总行程距离(TDD)的5%。在短距离环境中,该方法能够满足蛇形机器人在传统应用中进行自主导航和定位的要求,并且可以扩展到其他类似的多连杆机器人。