Robotic Path Planning and Task Execution

This module provides an introduction to the course and covers path planning, including topics such as graph traversal using Breadth-First Search (BFS), Dijkstra's algorithm, A*, and the implementation of a planner. Additionally, learners will have the opportunity to engage in activities and explore the significance of planning on graphs.

In this module, learners will delve into randomized planning and collision avoidance, focusing on the RRT algorithm and collision checking. Hands-on activities involve the implementation of RRT and line-based collision checking, enabling practical application of the concepts learned.

Behavior Trees module introduces learners to behavior trees, parallel nodes, decorators, blackboards, and sequence and selector nodes. With a hands-on approach, participants will implement behavior trees, mapping, and navigation with behavior trees, gaining practical experience in this area.

This module explores basic manipulation techniques, covering relevant topics and practical applications in the context of autonomous mobile manipulation behavior. Learners will acquire essential skills related to basic manipulation and its significance in robotic control.

Concluding the course, the Final Project module provides an extensive opportunity for learners to apply their knowledge and skills acquired throughout the course. The focus is on a robotics specialization final project, allowing for the practical demonstration of proficiency in robotic path planning and task execution.