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In this session we will cover the technical challenges with fielding autonomous mobile manipulation robots. These challenges range from hardware, to infrastructure software, data management and machine learning. Attendees will gain an understanding of the current state of the art in autonomous manipulation and future issues that remain to be addressed. With growing labor shortages, more businesses in logistics and manufacturing are seeking to automate operations. With recent advances in capabilities, autonomous robots present an attractive option given their ability to work within existing human-friendly processes and infrastructure. IAM Robotics has created and deployed, Swift, the world's first autonomous mobile picking robot, which navigates, identifies and picks items, using real-time computer vision. Swift robots rely on GPU computing to run novel RapidVision algorithms developed by IAM Robotics to perform these tasks. In this session we will discuss which technologies proved to be the most vital for fielding Swift robots and which were less important. We will also discuss next steps and new work to be done in autonomous mobile manipulation.
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