Lectures related to Global Navigation: Path Planning

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Graph Algorithms: Memory Management and Traversal

Explores memory management, graph representation, and traversal algorithms in Python, emphasizing BFS and DFS.

Graph Algorithms: Modeling and Traversal

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Graph Algorithms: Basics

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.

Navigation: Basics of Mobile Robotics

Covers obstacle avoidance and navigation strategies in mobile robotics using sensors and potential fields.

Search Algorithms: Abductive Reasoning

Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.

Robot Learning and Control

Covers learning and adaptive control for robots, focusing on real-time reactivity and path planning using dynamical systems.

Basics of Mobile Robotics: Components and Control

Covers the components and challenges of mobile robot control, including mechanics, locomotion, sensors, and architectures.

Learning and Adaptive Control for Robots: Overview and Path Planning

Explores learning and adaptive control for robots, focusing on challenges, path planning with dynamical systems, and real-time planning applications.

Graph Algorithms: BFS and DFS

Explores graph algorithms like BFS and DFS, discussing shortest paths, spanning trees, and data structures' role.

Graph Algorithms: Ford-Fulkerson and Strongly Connected Components

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

Paths, Diffusion, and Navigation

Explores paths in networks, brain connectivity, shortest path routing, network efficiency, navigation, and upcoming midterm.

Basics of Mobile Robotics: Uncertainties

Explores the basics of mobile robotics, emphasizing uncertainties and the Bayes filter algorithm.

Algorithms: Problem Solving and Graph Algorithms

Covers elementary graph algorithms, a midterm exam on algorithmic problem-solving, and distance measurement between strings.

Compliant Control for Robots: Impedance and Variable Stiffness

Explores compliant control for robots through impedance and variable stiffness, enabling safe and adaptive interactions with the environment.

Vision-Language-Action Models: Training and Applications

Delves into training and applications of Vision-Language-Action models, emphasizing large language models' role in robotic control and the transfer of web knowledge. Results from experiments and future research directions are highlighted.

Introduction: GNSS Signals and Modulations

Covers the generation and processing of GNSS signals from satellites to Earth.

Learning Physically-Consistent Gaussian Mixture Model

Explores Physically-Consistent Gaussian Mixture Models for robot control and trajectory learning.

GNSS for Space Applications

Covers the use of GNSS for space applications, including navigation, low-cost solutions, and real-time examples.

Robots: Safe Collaboration

Covers challenges and solutions for robots to work safely with humans, emphasizing adaptability and predictability.