Advancements in amphibious robot navigation through wheeled odometer uncertainty extension and distributed information fusion

IF 4.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Mingxuan Ding , Qinyun Tang , Kaixin Liu , Xi Chen , Dake Lu , Changda Tian , Liquan Wang , Yingxuan Li , Gang Wang
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Abstract

The advancement and safeguarding of the water-land interface region is of paramount importance, and amphibious robots with the capacity for autonomous operation can play a pivotal role in this domain. However, the inability of the majority of reliable navigation sensors to adapt to the water-land interface environment presents a significant challenge for amphibious robots, as obtaining positional information is crucial for autonomous operation. To address this issue, we have proposed a positioning and navigation framework, designated as NAWR (Navigation Algorithm for Amphibious Wheeled Robots), with the objective of enhancing the navigation capabilities of amphibious robots. Firstly, a method for representing the odometer's confidence based on a simplified wheel-terrain interaction model has been developed. This method quantitatively assesses the reliability of each odometer by estimating the slip rate. Secondly, we have introduced an improved split covariance intersection filter (I-SCIF), which maximizes the utilization of navigation information sources to enhance the accuracy of positional estimation. Finally, we will integrate these two methods to form the NAWR framework and validate the effectiveness of the proposed methods through multiple robot field trials. The results from both field trials and ablation tests collectively demonstrate that the modules and overall approach within the NAWR framework effectively enhance the navigation capabilities of amphibious robots.
通过轮式里程表不确定性扩展和分布式信息融合推进两栖机器人导航
水陆交界地区的进步和保护至关重要,而具有自主操作能力的两栖机器人可以在这一领域发挥关键作用。然而,大多数可靠的导航传感器都无法适应水陆交界环境,这给两栖机器人带来了巨大挑战,因为获取定位信息对于自主操作至关重要。为了解决这个问题,我们提出了一个定位和导航框架,命名为 NAWR(两栖轮式机器人导航算法),目的是提高两栖机器人的导航能力。首先,基于简化的车轮与地形相互作用模型,开发了一种表示里程表可信度的方法。这种方法通过估算滑移率来定量评估每个里程表的可靠性。其次,我们引入了改进的分裂协方差交叉滤波器(I-SCIF),最大限度地利用导航信息源来提高位置估计的准确性。最后,我们将整合这两种方法,形成 NAWR 框架,并通过多个机器人现场试验验证所提方法的有效性。实地试验和烧蚀测试的结果共同证明,NAWR 框架内的模块和整体方法可有效提高两栖机器人的导航能力。
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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