This lecture overviews Self-Awareness that has many applications in in Autonomous Systems and robotics. It covers the following topics in detail: Self-awareness definition, Self-aware systems, Cognitive architecture. Should you require access to the resource, please contact the author directly.
This lecture overviews LiDAR principles and technology. Active 3D shape reconstruction methods. Time-of-Flight principle. Pulsed wave. Continuous-wave propagation. Laser ToF Technology: LiDAR. LiDAR in Autonomous Systems: cars, drones. Drone LiDARs (Technical Specifications of Current Model, Alternatives for potential upgrade). Radio wave Technology: Radar. Sonar. Should you require access to the resource, please contact the author… Continue reading LiDAR in Robotics and Autonomous Systems
This lecture overviews Autonomous Systems Sensors that has many applications in Autonomous robots, cars, vessels and drones. It covers the following topics in detail: GPS, RTK-GPS, IMU, RFID Sensors, mono/stereo and event cameras, lidars, inductive/capacitance proximity sensors, Ultrasonic sensors. Should you require access to the resource, please contact the author directly.
In this lecture focused on Transformers in the field of computer vision, the limitations of Convolutional Neural Networks (CNNs) are emphasized. While CNNs have been the dominant architecture for visual tasks, they face challenges in capturing long-range dependencies and handling variable-sized inputs. However, recent research has shown promising results by combining convolutional layers with attention… Continue reading Attention and Transformers Networks in Computer Vision
A fully autonomous system can: a) gain information about the environment, b) work for an extended period without human intervention, c) move either all or part of itself throughout its operating environment without human assistance and d) avoid situations that are harmful to people, property, or itself unless those are part of its design specifications.… Continue reading Introduction to Autonomous Systems
This lecture overviews the relation between matter and system complexity on one hand and Life, Intelligence and Environment on the other one. First the theoretical tools (systems, graph and network theory) are overviewed. Then their relation to: a) life structure, c) biological neural networks, c) AI and artificial neural networks, d) social structure and evolution… Continue reading AI, System Complexity, Life, Intelligence and Environment