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learningguideReading CMU 07-380

Reading CMU 07-380 HW2: Classical and Motion Planning, from Robot-Cook PDDL to RRT* to Graphing LPs

07-380 HW2 has three parts. The programming assignment has you write PDDL for a pancake-cooking robot, solve it optimally with unified-planning and Fast Downward, then implement RRT and RRT* in rrt.py (Q2–Q7). The written part covers GraphPlan, one LP modeling problem, and two LP graphing problems. A Gradescope online component is CMU-only. This guide covers structure, prerequisites, and running the local autograder; it contains no solutions.

#cmu#07-380#ai-course#course-guide#planning#rrt#linear-programming
learningguideReading CMU 07-380

Reading CMU 07-380 Lecture 4: Motion Planning, RRT Samples Its Way Through Continuous Space

The second half of 07-380 Lec4 moves planning into continuous configuration space. States can no longer be enumerated, so RRT samples a random point, extends the nearest tree node a short step toward it, and checks the whole segment for collisions. RRT is probabilistically complete but not optimal; RRT* uses tree path costs to pick a better parent and rewire neighbors, so the path converges to optimal as samples grow.

#cmu#07-380#ai-course#course-guide#motion-planning#rrt