Deep Learning for Automated Systems: From the Warehouse to the Road - PowerPoint PPT Presentation

Sep 03, 2022 •384 likes •672 views

Deep Learning for Automated Systems: From the Warehouse to the Road Dr. Melissa C. Smith Clemson University Future Computing Technologies Laboratory Eddie Weill, Sufeng Niu, Colin Targonski, and Ben Shealy Overview Simulation Using deep

Deep Learning for Automated Systems: From the Warehouse to the Road Dr. Melissa C. Smith Clemson University Future Computing Technologies Laboratory Eddie Weill, Sufeng Niu, Colin Targonski, and Ben Shealy
Overview
Simulation Using deep learning in a simulated environment
The Need for a Simulator
Deep Learning in a Simulator Webpage: http://www.carla.org/ Paper: Dosovitskiy, Alexey, et al. "CARLA: An open urban driving simulator." arXiv preprint arXiv:1711.03938 (2017).
Perception Developing perception for automated systems
Autonomous Driving Perception
Autonomous Driving Perception
Autonomous Driving Perception Tetreault, Jesse. Deep Multimodal Fusion Networks for Semantic Segmentation . Diss. Clemson University, 2017.
Perception on Embedded Devices Redmon, Joseph, et al. "You only look once: Unified, real-time object detection." Synthetic Image Proceedings of the IEEE conference on computer vision and pattern recognition . 2016. Training Detector OCR Detections Network (i.e. Extracted Text Extraction YOLO, SSD) Acknowledgement goes to BMW ITRC for partnering on this endeavor and providing the data for experimentation Luckow, Andre, et al. "Deep learning in the automotive industry: Applications and tools." Big Data (Big Data), 2016 IEEE International Conference on . IEEE, 2016.
Perception + Control Integrating perception with reinforcement learning
Autonomous Driving in CARLA Action (Steering / Acceleration) Combine Feature Maps Rewards Reinforcement Learning Agent Environment “Approaching Stop Sign” (Carla) “Light is Yellow” “Car stopped at intersection” State (RGB Image) Segmentation Traffic Interpretation Object Detection
Autonomous Driving in CARLA
Planning Using reinforcement learning to explore environments
Neural Network Based Planning VIN GVIN 16 x 16 2D Maze New York City Street Map (13K intersections) A. Tamar, et al. Value Iteration Networks . NIPS, 2016. S. Niu, et al. Generalized Value Iteration Network: Life Beyond Lattices . 32nd AAAI, 2018.
Neural Network Based Planning G S Social network reasoning Navigation Knowledge querying Network routing
Neural Network Based Planning (GVIN) Start Goal
Neural Network Based Planning (GVIN) Testing Training Testing 10 nodes 2642 nodes 5069 nodes S. Niu, et al. Generalized Value Iteration Network: Life Beyond Lattices . 32nd AAAI, 2018.
Distributed Computing Scaling beyond a single HPC cluster
Clemson University’s Palmetto Cluster
Is One HPC Cluster Enough? www.nlm.nih.gov Image credit: http://harborresearch.com/connected-vehicles-rise-transportation-ecosystems/
Scientific Data Analysis at Scale (SciDAS) NSF Award No. 1659300
Scientific Data Analysis at Scale (SciDAS) NSF Award No. 1659300
Scientific Data Analysis at Scale (SciDAS) NSF Award No. 1659300
Scientific Data Analysis at Scale (SciDAS) NSF Award No. 1659300
Scientific Data Analysis at Scale (SciDAS) NSF Award No. 1659300
Wrap Up
Thank you! Questions?

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