LeetCode in Kotlin

874. Walking Robot Simulation

Medium

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:

Some of the grid squares are obstacles. The ith obstacle is at grid point obstacles[i] = (xi, yi). 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:

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).

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).

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).

The furthest point the robot ever gets from the origin is (0, 6), which squared is 62 = 36 units away.

Constraints:

Solution

class Solution {
    internal class Point(var row: Int, var column: Int) {
        override fun equals(other: Any?): Boolean {
            if (other !is Point) {
                return false
            }
            return other.row == row && other.column == column
        }

        override fun hashCode(): Int {
            return row * column * 31
        }
    }

    internal enum class Direction(val x: Int, val y: Int) {
        NORTH(0, 1) {
            override fun turnLeft(): Direction {
                return WEST
            }

            override fun turnRight(): Direction {
                return EAST
            }
        },
        EAST(1, 0) {
            override fun turnLeft(): Direction {
                return NORTH
            }

            override fun turnRight(): Direction {
                return SOUTH
            }
        },
        SOUTH(0, -1) {
            override fun turnLeft(): Direction {
                return EAST
            }

            override fun turnRight(): Direction {
                return WEST
            }
        },
        WEST(-1, 0) {
            override fun turnLeft(): Direction {
                return SOUTH
            }

            override fun turnRight(): Direction {
                return NORTH
            }
        };

        abstract fun turnLeft(): Direction
        abstract fun turnRight(): Direction
        fun next(p: Point): Point {
            return Point(p.row + x, p.column + y)
        }
    }

    fun robotSim(commands: IntArray, obstacles: Array<IntArray>): Int {
        val set: MutableSet<Point> = HashSet()
        for (i in obstacles.indices) {
            val p = Point(obstacles[i][0], obstacles[i][1])
            set.add(p)
        }
        var direction = Direction.NORTH
        var p = Point(0, 0)
        var maxDistance = 0
        for (i in commands.indices) {
            val command = commands[i]
            if (command == -1) {
                direction = direction.turnRight()
                continue
            }
            if (command == -2) {
                direction = direction.turnLeft()
                continue
            }
            for (j in 0 until command) {
                val destination = direction.next(p)
                if (set.contains(destination)) {
                    break
                }
                p = destination
            }
            maxDistance = maxDistance.coerceAtLeast(p.row * p.row + p.column * p.column)
        }
        return maxDistance
    }
}