首页|New Robotics Findings from Zhejiang University Discussed (X-slam: Scalable Dense Slam for Task-aware Optimization Using Csfd)
New Robotics Findings from Zhejiang University Discussed (X-slam: Scalable Dense Slam for Task-aware Optimization Using Csfd)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news reporting originating from Hangzhou, People’s Republ ic of China, by NewsRx correspondents, research stated, “We present X-SLAM, a re al-time dense differentiable SLAM system that leverages the complex-step finite difference (CSFD) method for efficient calculation of numerical derivatives, byp assing the need for a large-scale computational graph. The key to our approach i s treating the SLAM process as a differentiable function, enabling the calculati on of the derivatives of important SLAM parameters through Taylor series expansi on within the complex domain.”
HangzhouPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningRoboticsRobotsZhejiang University
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