Question 1

How does A* Search guarantee the shortest path?

Accepted Answer

A* Search evaluates candidate nodes using the evaluation function f(n) = g(n) + h(n), where g(n) is the exact cost from the start node to node n, and h(n) is an admissible heuristic estimate to the target (such as Manhattan or Euclidean distance). As long as h(n) never overestimates the true remaining distance, A* is mathematically guaranteed to return the optimal shortest path while exploring far fewer nodes than unguided Dijkstra.

Question 2

What is 2D LiDAR SLAM Occupancy Grid Mapping?

Accepted Answer

Simultaneous Localization and Mapping (SLAM) with LiDAR casts 360-degree laser distance rays from an autonomous rover. As the rover moves through an unmapped room, raycasting updates grid cells using Bayesian probability: cells traversed by laser rays are classified as Free Space (white), while cells where laser pulses terminate are marked as Occupied Walls (red), progressively building a full spatial map.

Question 3

What is Artificial Potential Field (APF) navigation?

Accepted Answer

Artificial Potential Field navigation models the robot as a charged particle navigating an artificial energy landscape. The goal destination exerts an attractive potential pulling the robot forward, while obstacles generate repulsive potential gradients pushing the robot away. The robot navigates by following the resultant vector force (gradient descent).

Question 4

Why are visual Stack and Queue animations important for computer science?

Accepted Answer

Data structures like Stacks (Last-In First-Out / LIFO) and Queues (First-In First-Out / FIFO) form the bedrock of algorithm design. Visualizing push/pop and enqueue/dequeue operations helps learners understand function call frames, memory management, and breadth-first search pipelines.

AI, SLAM Mapping & Graph Search Lab

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