首页|Findings from Tsinghua University Provides New Data on Robotics (A Robust Robot Perception Framework for Complex Environments Using Multiple Mmwave Radars)
Findings from Tsinghua University Provides New Data on Robotics (A Robust Robot Perception Framework for Complex Environments Using Multiple Mmwave Radars)
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Research findings on Robotics are disc ussed in a new report. According to news reporting out of Beijing, People's Repu blic of China, by NewsRx editors, research stated, "The robust perception of env ironments is crucial for mobile robots to operate autonomously in complex enviro nments. Over the years, mobile robots mainly rely on optical sensors for percept ion, which degrade severely in adverse weather conditions." Our news journalists obtained a quote from the research from Tsinghua University , "Recently, singlechip millimeter-wave (mmWave) radars have been widely used f or mobile perception, owing to their robustness to all-weather conditions, light weight design, and low cost. However, existing research based on mmWave radars p rimarily focuses on single radar and single task. Due to the limited field of vi ew and sparse observation, perception based on a single radar may not ensure the required robustness in complex environments. To address this challenge, we prop ose a novel robust perception framework for robots in complex environments based on multiple mmWave radars, named MMR-PFR. The framework integrates three critic al tasks for robots, including ego-motion estimation, multi-radar fusion mapping , and dynamic target state estimation. Multiple tasks collaborate and facilitate each other to improve overall performance. In the framework, we propose a new m ulti-radar point cloud fusion method to generate a more accurate environmental m ap. In addition, we propose a new online calibration algorithm for multiple rada rs to ensure the long-term reliability of the system. To evaluate MMR-PRF, we bu ild a prototype and carry out experiments in real-world scenarios."
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningNano-robotRobotRoboticsTsinghu a University
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