Robot Motion Planning: Search Methods, Sampling, and Guarantees

All flashcards

What is motion planning?

A computational problem of finding a valid sequence of configurations that moves an object from a source to a destination, typically while avoiding obstacles and respecting constraints.

What is configuration space?

The set of all possible configurations of a robot. Each point in this space represents one complete robot pose or state for the planning problem.

What is free space?

The subset of configuration space, $C_{free}$, containing configurations in which the robot does not collide with obstacles.

Why does a planar robot that can rotate need three configuration parameters?

It needs two coordinates for translation, $x$ and $y$, plus an angle $\theta$ for orientation.

What is a sub-goal in local motion planning?

A visible intermediate target in the robot's local area. A sequence of sub-goals can guide the robot toward a final target that it cannot currently observe.

Quiz questions

1. What is a common trade-off when choosing a coarse grid for motion planning?Answer: It reduces the number of points to search but may miss narrow passages.
2. In interval-based search, what does a route entirely inside $X^{-}$ establish?Answer: The route is feasible in $C_{free}$.
3. What is a major limitation of an ordinary artificial potential-field planner?Answer: It can become trapped at a local minimum before reaching the goal.
4. What does probabilistic completeness mean for a sampling-based planner?Answer: With more planning effort, its probability of missing an existing solution approaches zero.
5. When is a reusable roadmap especially useful compared with a tree-growing planner?Answer: When many start-and-goal queries use the same environment.