  Understanding how robots plan and execute tasks is crucial in today's world,
where they are becoming more prevalent in our daily lives. However, teaching
non-experts the complexities of robot planning can be challenging. This work
presents an open-source platform that simplifies the process using a visual
interface that completely abstracts the complex internals of hierarchical
planning that robots use for performing task and motion planning. Using the
principles developed in the field of explainable AI, this intuitive platform
enables users to create plans for robots to complete tasks, and provides
helpful hints and natural language explanations for errors. The platform also
has a built-in simulator to demonstrate how robots execute submitted plans.
This platform's efficacy was tested in a user study on university students with
little to no computer science background. Our results show that this platform
is highly effective in teaching novice users the intuitions of robot task
planning.
