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Learning From Roomba Style Problem Solving

Several months back, I watched my Roomba make a map of the second floor of my house. That process looked like this:

  1. Take off in a straight line.
  2. Hit an object (like a wall).
  3. Back up.
  4. Make a random turn.
  5. Go back to step 1.

It’s surprisingly entertaining to watch. The Roomba seems determined to clean every inch, but its method is simple: move forward until you can’t, adjust, and try again. There’s a certain charm to its relentless, trial-and-error approach.

The Roomba’s Algorithm and Problem Solving

The Roomba’s seemingly random path is guided by a sophisticated algorithm designed to ensure it covers the entire floor efficiently. This method is called a “random bounce” algorithm, and it is surprisingly effective for simple navigation tasks in a household setting.1 However, it also highlights a broader principle: navigating through uncertainty by trial and error.

Parallels to Problem Solving in Our Industry

Starting a consulting contract with a new client sometimes mirrors Roomba’s problem-solving approach when faced with challenges, and it occurred to me that this also maps to how the industry tackles problems. Here’s a closer look at this analogy:

  1. Starting Straight: When tackling a new problem, we often begin with a straightforward plan. This is akin to the Roomba starting its journey in a straight line. We have our objectives clear and our path defined.
  2. Encountering Obstacles: We encounter obstacles inevitably, whether technical issues, regulatory hurdles, or market shifts. Like the Roomba bumping into a wall, these challenges force us to reassess our course.
  3. Backing Up: After encountering resistance, we analyze what went wrong. This reflective process is crucial for understanding the nature of the obstacle and determining how to address it.
  4. Random Turns and New Directions: The next step is to pivot or adjust our approach. My Roomba randomly turns and tries a new direction, but we must be intentional here and explore different solutions, sometimes through brainstorming sessions, consultations, or iterative testing.
  5. Iterative Process: We repeat this process, continually adjusting and refining our strategies. Each cycle helps us map out the problem space more thoroughly, much like the Roomba gradually creating a complete floor map.

Embracing the Process

While it might seem inefficient sometimes, this iterative process is essential for innovation and problem-solving. Here are a few takeaways from the Roomba analogy:

  • Persistence: Keep moving. Just as the Roomba doesn’t stop when it hits a wall, we must persist despite setbacks.
  • Adaptability: Be willing to change direction. Our flexibility in approach allows us to navigate obstacles and discover new opportunities.
  • Reflection: Take time to back up and analyze. Understanding why something didn’t work is as important as finding what does work.

The one change to make

The one problem with this problem solving method is that things can get overlooked. In the case of my Roomba, that would be the 90% of the room that doesn’t constitute a wall or other obstacle. As CNET noted: “Spots in tight places (corners, table and chair legs) get lots of repeat attention. Open areas, however, are likely vacuumed once (or perhaps not at all) since the robot travels in a straight line until it detects something in its path.”2 Robot vacuums use sensors to detect dirt so that dirty areas that aren’t near obstacles get the attention that they need. Likewise, we must remain cognizant of how our solutions are working overall, or the changes made to overcome obstacles will undo our progress.

Conclusion

Watching the Roomba navigate my house has been a fascinating reminder of how problem-solving often works in our industry. It’s a process of continuous movement, adjustment, and learning. While the path may seem unpredictable, each turn and pivot brings us closer to our goals. So next time you hit a wall in your project, remember the Roomba: back up, turn, and keep going.

Footnotes

  1. Chris Woodford, How Do Roomba Robot Vacuum Cleaners Work?, Explain that Stuff (2009), http://www.explainthatstuff.com/how-roomba-works.html (last visited Sep 18, 2024). ↩︎
  2. Brian Bennett, ​This is why your Roomba’s random patterns actually make perfect sense​, CNET (2021), https://www.cnet.com/home/kitchen-and-household/this-is-why-your-roombas-random-patterns-actually-make-perfect-sense/ (last visited Apr 18, 2024). ↩︎

Mickey
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