Walking Robot Simulation II
A medium-tier problem at 25% community acceptance, tagged with Design, Simulation. Reported in interviews at Block and 0 others.
Walking Robot Simulation II is a medium-difficulty design and simulation problem with a 25% acceptance rate. Block has asked it. This isn't a brute-force grid traversal. It's about understanding state management, boundary wrapping, and how to track position and direction efficiently without simulating every step. If you hit this live and your first instinct is to walk the robot through all N steps, you'll time out. That's the trap. StealthCoder surfaces the pattern in seconds if you blank on the optimization during the OA.
Companies that ask "Walking Robot Simulation II"
Walking Robot Simulation II is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core trick is recognizing that a robot moving in a 4x4 grid will eventually cycle. Instead of simulating every step, you detect the cycle and use modulo arithmetic to jump to the final position. The challenge is tracking direction changes, handling boundary wrapping correctly, and avoiding off-by-one errors in your cycle detection. Most candidates start by literally stepping the robot and hit time limits. The pattern requires you to think about state space (position and direction combined) and when that state repeats. Once you see the cycle, the problem collapses. StealthCoder is your hedge if the simulation-to-cycle jump pattern doesn't click during the assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Walking Robot Simulation II recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Walking Robot Simulation II interview FAQ
Is this just a straightforward grid simulation?+
No. A naive step-by-step simulation will time out on large step counts. You need to detect when the robot's state (position and direction) repeats and use that cycle to skip ahead. That's what separates AC from TLE.
How does direction handling affect the solution?+
Direction changes matter because they define the state. The robot can face four directions, and each affects where it moves next. Your cycle detection must track position AND direction together, not just position alone.
Why is this a design problem, not just simulation?+
You're designing a system that tracks robot state efficiently. It's about choosing the right data structures and algorithms to represent position, direction, and detect cycles, not just coding a walk loop.
What's the acceptance rate telling me?+
25% acceptance is low-medium. The cycle detection pattern isn't obvious, and boundary wrapping and off-by-one errors trip people up. It rewards careful state management and testing edge cases.
Why did Block ask this in interviews?+
It tests your ability to optimize beyond the obvious approach, handle state machines, and think about efficiency under constraint. Those skills matter in production systems at payment and commerce companies.
Want the actual problem statement? View "Walking Robot Simulation II" on LeetCode →