. Walking Robot Simulation

874. Walking Robot Simulation

Difficulty: Medium

Topics: Array, Hash Table, Simulation

A robot on an infinite XY-plane starts at point (0, 0) facing north. The robot can receive a sequence of these three possible types of commands:

• -2: Turn left 90 degrees.
• -1: Turn right 90 degrees.
• 1 <= k <= 9: Move forward k units, one unit at a time.

Some of the grid squares are obstacles. The ith obstacle is at grid point obstacles[i] = (x_i, y_i). If the robot runs into an obstacle, then it will instead stay in its current location and move on to the next command.

Return _the maximum Euclidean distance that the robot ever gets from the origin squared (i.e. if the distance is 5, return 25).

Note:

• North means +Y direction.
• East means +X direction.
• South means -Y direction.
• West means -X direction.
• There can be obstacle in [0,0].

Example 1:

• Input: commands = [4,-1,3], obstacles = []
• Output: 25
• Explanation: The robot starts at (0, 0):
  1. Move north 4 units to (0, 4).
  2. Turn right.
  3. Move east 3 units to (3, 4).
  4. The furthest point the robot ever gets from the origin is (3, 4), which squared is 32 + 42 = 25 units away.

Example 2:

• Input: commands = [4,-1,4,-2,4], obstacles = [[2,4]]
• Output: 65
• Explanation: The robot starts at (0, 0):
  1. Move north 4 units to (0, 4).
  2. Turn right.
  3. Move east 1 unit and get blocked by the obstacle at (2, 4), robot is at (1, 4).
  4. Turn left.
  5. Move north 4 units to (1, 8).
  6. The furthest point the robot ever gets from the origin is (1, 8), which squared is 12 + 82 = 65 units away.

Example 3:

• Input: commands = [6,-1,-1,6], obstacles = []
• Output: 36
• Explanation: The robot starts at (0, 0):
  1. Move north 6 units to (0, 6).
  2. Turn right.
  3. Turn right.
  4. Move south 6 units to (0, 0).
  5. The furthest point the robot ever gets from the origin is (0, 6), which squared is 62 = 36 units away.

Constraints:

• 1 <= commands.length <= 10⁴
• commands[i] is either -2, -1, or an integer in the range [1, 9].
• 0 <= obstacles.length <= 10⁴
• -3 * 10⁴ <= x_i, y_i <= 3 * 10⁴
• The answer is guaranteed to be less than 2³¹

Solution:

We need to simulate the robot's movement on an infinite 2D grid based on a sequence of commands and avoid obstacles if any. The goal is to determine the maximum Euclidean distance squared that the robot reaches from the origin.

Approach

1. Direction Handling:

   • The robot can face one of four directions: North, East, South, and West.
   • We can represent these directions as vectors:
     • North: (0, 1)
     • East: (1, 0)
     • South: (0, -1)
     • West: (-1, 0)

2. Turning:

   • A left turn (-2) will shift the direction counterclockwise by 90 degrees.
   • A right turn (-1) will shift the direction clockwise by 90 degrees.

3. Movement:

   • For each move command, the robot will move in its current direction, one unit at a time. If it encounters an obstacle, it stops moving for that command.

4. Tracking Obstacles:

   • Convert the obstacles list into a set of tuples for quick lookup, allowing the robot to quickly determine if it will hit an obstacle.

5. Distance Calculation:

   • Track the maximum distance squared from the origin that the robot reaches during its movements.

Let's implement this solution in PHP: 874. Walking Robot Simulation

  
  
  Explanation:




Direction Management: We use a list of vectors to represent the directions, allowing easy calculation of the next position after moving.

Obstacle Detection: By storing obstacles in a set, we achieve O(1) time complexity for checking if a position is blocked by an obstacle.

Distance Calculation: We continuously update the maximum squared distance the robot reaches as it moves.



  
  
  Test Cases



The example test cases provided are used to validate the solution:



[4,-1,3] with no obstacles should return 25.

[4,-1,4,-2,4] with obstacles [[2,4]] should return 65.

[6,-1,-1,6] with no obstacles should return 36.







This solution efficiently handles the problem constraints and calculates the maximum distance squared as required.

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