How do you solve Walking Robot Simulation II on LeetCode?

Walking Robot Simulation II (LeetCode #2069) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: The robot only moves along the perimeter of the grid, which can be leveraged to optimize the movement calculations.

What is the brute force solution for Walking Robot Simulation II?

The brute force approach for Walking Robot Simulation II is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach simulates each step the robot takes, checking if it can move forward or needs to turn. It directly follows the robot's movement rules without optimization. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Walking Robot Simulation II?

Walking Robot Simulation II uses the following concepts: Design, Simulation. The recommended patterns to study are: Simulation, Modular Arithmetic.

What are the interview tips for Walking Robot Simulation II?

Always consider edge cases, such as moving out of bounds. Think about how to reduce the number of operations, especially when dealing with repeated actions. Explain your thought process clearly, especially when transitioning from brute force to optimization.

What are common mistakes when solving Walking Robot Simulation II?

Failing to account for the direction change when hitting boundaries. Not using modular arithmetic to optimize the number of steps.

#2069

Walking Robot Simulation II

Medium

DesignSimulationSimulationModular Arithmetic

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(1)

💡

Intuition

Time O(n)Space O(1)

Instead of simulating each step, we can calculate the final position using modular arithmetic based on the perimeter of the grid. This allows us to determine the robot's position and direction efficiently.

⚙️

Algorithm

3 steps

1Step 1: Calculate the perimeter of the grid as 2 * (width + height).
2Step 2: Use the total steps modulo the perimeter to find the effective steps the robot takes.
3Step 3: Determine the final position and direction based on the effective steps.

solution.py38 lines

1class Robot:
2    def __init__(self, width: int, height: int):
3        self.width = width
4        self.height = height
5        self.perimeter = 2 * (width + height)
6        self.x, self.y = 0, 0
7        self.directions = ['East', 'North', 'West', 'South']
8        self.dir_index = 0
9
10    def step(self, num: int):
11        effective_steps = num % self.perimeter
12        for _ in range(effective_steps):
13            if self.dir_index == 0:
14                if self.x + 1 < self.width:
15                    self.x += 1
16                else:
17                    self.dir_index = 1
18            elif self.dir_index == 1:
19                if self.y + 1 < self.height:
20                    self.y += 1
21                else:
22                    self.dir_index = 2
23            elif self.dir_index == 2:
24                if self.x - 1 >= 0:
25                    self.x -= 1
26                else:
27                    self.dir_index = 3
28            else:
29                if self.y - 1 >= 0:
30                    self.y -= 1
31                else:
32                    self.dir_index = 0
33
34    def getPos(self):
35        return [self.x, self.y]
36
37    def getDir(self):
38        return self.directions[self.dir_index]

ℹ

Complexity note: The time complexity is O(n) because we only loop through the effective steps, which is at most the perimeter of the grid. The space complexity is O(1) since we only use a fixed amount of space.

1The robot only moves along the perimeter of the grid, which can be leveraged to optimize the movement calculations.
2Using modular arithmetic allows for quick determination of the robot's position after many steps.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.