Deep Learning for Robot Perception and Cognition

Teaches readers how to apply deep learning principles to robot vision and perception

Alexandros Iosifidis (Edited by), Anastasios Tefas (Edited by)

9780323857871, Elsevier Science

Paperback / softback, published 10 March 2022

634 pages, 55 illustrations (15 in full color)
23.5 x 19 x 3.9 cm, 1.31 kg

Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks.

1. Introduction 2. Neural Networks and Backpropagation 3. Convolutional Neural Networks 4. Graph Convolutional Networks 5. Recurrent Neural Networks 6. Deep Reinforcement Learning 7. Lightweight Deep Learning 8. Knowledge Distillation 9. Progressive and Compressive Deep Learning 10. Representation Learning and Retrieval 11. Object Detection and Tracking 12. Semantic Scene Segmentation for Robotics 13. 3D Object Detection and Tracking 14. Human Activity Recognition 15. Deep Learning for Vision-based Navigation in Autonomous Drone Racing 16. Robotic Grasping in Agile Production 17. Deep learning in Multiagent Systems 18. Simulation Environments 19. Biosignal time-series analysis 20. Medical Image Analysis 21. Deep learning for robotics examples using OpenDR

Subject Areas: Neural networks & fuzzy systems [UYQN], Artificial intelligence [UYQ], Robotics [TJFM1], Automatic control engineering [TJFM]