首页|New Findings in Robotics Described from Massachusetts Institute of Technology (G mmap: Memory-efficient Continuous Occupancy Map Using Gaussian Mixture Model)
New Findings in Robotics Described from Massachusetts Institute of Technology (G mmap: Memory-efficient Continuous Occupancy Map Using Gaussian Mixture Model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news reporting originating in Cambridge, Massachus etts, by NewsRx journalists, research stated, “Energy consumption of memory acce sses dominates the compute energy in energy-constrained robots, which require a compact 3- D map of the environment to achieve autonomy. Recent mapping framework s only focused on reducing the map size while incurring significant memory usage during map construction due to the multipass processing of each depth image.”
CambridgeMassachusettsUnited StatesNorth and Central AmericaEmerging TechnologiesMachine LearningNano-robotRoboticsMassachusetts Institute of Technology
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