Beyond 2020—Vision SoCs for the Edge - Part 2
Accelerating Intelligent SLAM Applications with the Synopsys ARC EV Processor and KudanSLAM
3:00 AM - 3:30 AM JST on Saturday, September 19
SYNOPSYS SEMINAR
Speakers
Simultaneous localization and mapping (SLAM) is used for building and updating a map of an unknown environment while keeping track of the viewpoint's location within it. Applications for SLAM include autonomous driving, augmented/virtual reality and robotics. When executed in parallel with a convolutional neural network (CNN) engine, SLAM applications can become more ‘intelligent,’ able to identify objects in the environment and make decisions based on what appears. Multiple open source (like ORB-SLAM2) and commercial SLAM algorithms can simplify implementation of SLAM functionality. Synopsys has collaborated with Kudan to accelerate their KudanSLAM product on Synopsys DesignWare ARC EV Processors. In this talk, we will describe how to offload a significant portion of the SLAM algorithm to the EV Processor to boost the algorithm’s performance, while simultaneously running an object detection graph on the EV’s CNN engine.
こんなんあるんですね。こういうウェビナーもっと見たい。
Beyond 2020—Vision SoCs for the Edge - Part 2
Accelerating Intelligent SLAM Applications with the Synopsys ARC EV Processor and KudanSLAM
3:00 AM - 3:30 AM JST on Saturday, September 19
SYNOPSYS SEMINAR
Speakers
Liliya Tazieva
Synopsys
Software Engineer
Description
Simultaneous localization and mapping (SLAM) is used for building and updating a map of an unknown environment while keeping track of the viewpoint's location within it. Applications for SLAM include autonomous driving, augmented/virtual reality and robotics. When executed in parallel with a convolutional neural network (CNN) engine, SLAM applications can become more ‘intelligent,’ able to identify objects in the environment and make decisions based on what appears. Multiple open source (like ORB-SLAM2) and commercial SLAM algorithms can simplify implementation of SLAM functionality. Synopsys has collaborated with Kudan to accelerate their KudanSLAM product on Synopsys DesignWare ARC EV Processors. In this talk, we will describe how to offload a significant portion of the SLAM algorithm to the EV Processor to boost the algorithm’s performance, while simultaneously running an object detection graph on the EV’s CNN engine.