首页|Shanghai University of Engineering Science Researcher Updates Current Data on Robotics (A tightly-coupled LIDAR-IMU SLAM method for quadruped robots)
Shanghai University of Engineering Science Researcher Updates Current Data on Robotics (A tightly-coupled LIDAR-IMU SLAM method for quadruped robots)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on robotics. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, "Aiming to address the issue of mapping failure resulting from unsmooth motion during SLAM (Simultaneous Localization and Mapping) performed by a quadruped robot, a tightly coupled SLAM algorithm that integrates LIDAR and IMU sensors is proposed in this paper." Funders for this research include Shanghai Science And Technology Innovation Action Plan High-tech Field Project. Our news editors obtained a quote from the research from Shanghai University of Engineering Science: "Firstly, the IMU information, after undergoing deviation correction, is utilized to remove point cloud distortion and serve as the initial value for point cloud registration. Subsequently, a registration algorithm based on Normal Distribution Transform (NDT) and sliding window is presented to ensure real-time positioning and accuracy. Then, an error function combining IMU and LIDAR is formulated using a factor graph, which iteratively optimizes position, attitude, and IMU deviation. Finally, loop closure detection based on Scan Context is introduced, and loop closure factors are incorporated into the factor graph to achieve effective mapping. An experimental platform is established to conduct accuracy and robustness comparison experiments."
Shanghai University of Engineering ScienceShanghaiPeople's Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningNano-robotRobotics
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