Practice A* Algorithm (Graph-Based Deterministic Planning) - 5.1.1 | Chapter 5: Motion Planning and Path Optimization | Robotics Advance
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5.1.1 - A* Algorithm (Graph-Based Deterministic Planning)

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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does f(n) represent in the A* algorithm?

💡 Hint: Think about how both g(n) and h(n) contribute to the pathfinding process.

Question 2

Easy

Is A* admissible if h(n) overestimates the cost?

💡 Hint: Consider the implications of using an inaccurate heuristic.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does the 'g(n)' term represent in the A* algorithm?

  • Estimated distance to the goal
  • Cost to reach node from the start
  • Total cost of the path

💡 Hint: Think about what cost entails in a pathfinding context.

Question 2

True or False: A* algorithm is guaranteed to find the optimal solution when h(n) is admissible.

  • True
  • False

💡 Hint: Recall the definition of admissibility in relation to the heuristic.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A grid map has the following costs associated with movements: Up = 2, Down = 3, Left = 1, Right = 1. Design a scenario where the A* algorithm must find the optimal path from the start to the goal considering obstacles.

💡 Hint: Consider how obstacles affect the cost and how to manipulate the heuristic for efficiency.

Question 2

Compare the performance of A against D in a logistics scenario where package delivery routes must be adjusted due to unexpected road closures.

💡 Hint: Focus on the trade-offs of recomputation versus incremental changes.

Challenge and get performance evaluation