基于差分轮移动机器人的SLAM算法对比研究

Research on SLAM Mapping Algorithm Based on Differential Wheel Mobile Robot

在自动驾驶和机器人产业蓬勃发展的背景下,对汽车和机器人环境进行高精度建图的重要性日益凸显。差分轮移动机器人以其较高的灵活性和较低的成本被广泛采用。差分轮移动机器人的核心技术——SLAM(即时定位与地图构建)算法,已经成为一个热门的研究课题。对差分轮移动机器人进行了基于Gmapping SLAM与Cartographer SLAM的建图质量研究。通过ROS中的Gazebo平台构建仿真室内场景,评估了两种算法在不同场景下表现差异。

In the context of the booming autonomous driving and robotics industry,the importance of high-precision mapping of automotive and robotic environments is becoming increasingly prominent.Differential wheel mobile robots are widely adopted due to their high flexibility and low cost.The core technology of differential wheel mobile robots,SLAM(real-time localization and mapping)algorithm,has become a hot research topic.The mapping quality of differential wheel mobile robot based on Gmapping SLAM and Cartographer SLAM was studied.By using the Gazebo platform to construct a simulated indoor scene in ROS,the performance differences of the two algorithms in different scenarios were evaluated.