Welcome to Vacuum Wars’ definitive guide to the best robot vacuums with obstacle avoidance in 2024! These selections are the result of our independent and non-sponsored evaluations, with a focus on how well these robots navigate around common obstacles like cords, furniture, and pet toys.
Weโve tested emerging technologies such as AI-powered vision, 3D sensors, and infrared systems to assess their effectiveness in real-world scenarios. Our rankings are continuously updated to reflect the latest test results and industry innovations, making it easier for you to select the ideal automated vacuum for your space.
Products that have been discontinued or are frequently out of stock are removed from our recommendations.
Overall Score: 98.3
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Overall Score: 97.7
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Overall Score: 97.3
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Overall Score: 97
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Overall Score: 85.8
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Overall Score: 74.9
Overall Score: 99.7
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Overall Score: 95.5
Overall Score: 93.4
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Overall Score: 68.8
Exploring the Evolution of Obstacle Avoidance in Robot Vacuums
In the early days, robot vacuums didnโt have any obstacle avoidance at all. The only way to ensure a smooth run was to clear any clutter off the floor before starting the vacuum โ a task thatโs still necessary with most budget-friendly models today. If you didnโt โrobot-proofโ your house, the vacuum was bound to get stuck on something.
At that time, the only sensor was a simple bump sensor. If the robot ran into something solid and heavy, the bump sensor would trigger, and the vacuum would move around the object. This worked reasonably well for avoiding furniture, but it didnโt help with smaller, lighter objects.
Soon, infrared (IR) sensors were added to most models. While these didnโt avoid obstacles outright, they helped the robot detect when it was approaching a wall or another large object, allowing for gentler navigation.
Then came the introduction of Lidar โ a spinning laser on top of the robot that greatly improved navigation. Lidar allowed robots to map their surroundings more accurately, but since the laser sits several inches off the ground, it couldnโt detect smaller objects or anything below the sensorโs height. As a result, these robots would still run over low-profile objects.
Our First Obstacle Avoidance Review
Vacuum Wars has been testing robot vacuums for years, including obstacle avoidance capabilities. The first robot vacuum Vacuum Wars tested with a dedicated obstacle avoidance system was the Ecovacs T8 AIVI in 2020. (Watch our review on YouTube) It used a front-facing camera to recognize and avoid obstacles, and it worked reasonably well for a first attempt. But it quickly became apparent that there were multiple ways to approach obstacle avoidance, each with its own strengths and weaknesses.
The Arrival of Obstacle Avoidance Systems
A few years ago, robot vacuums underwent a significant transformation. Manufacturers began introducing extra sensors that allowed these machines to detect and avoid household objects their traditional sensors couldn’t. This was a major improvement, as robot vacuums became far less likely to get stuck on, or worse, run over things like cords, toys, or pet waste โ the bane of many pet owners.
However, while this technology certainly enhanced the robot vacuum experience, these early obstacle avoidance systems were far from perfect. Now, almost five years after their initial release, itโs clear that manufacturers still havenโt settled on the optimal sensor arrangement or configuration. That said, we’re starting to see some promising trends and best practices emerge.
Current Obstacle Avoidance Systems
Hereโs a breakdown of the different obstacle avoidance systems we see today:
- Cameras: High-end robot vacuums often rely on cameras for obstacle avoidance. Early models, like the Ecovacs T8, used just one front-facing camera. These days, cameras are often paired with other sensors for better results.
- Crossed IR Sensors: These focused beams of infrared light cross in front of the robot, helping it avoid obstacles in their path. This system has become extremely popular and is often found on mid-to-high-end models.
- 3D Structured Light: This system projects a light pattern onto the environment and detects obstacles by analyzing how the light is distorted. Structured light is often paired with cameras and crossed lasers for a more comprehensive solution.
- Time of Flight (ToF) Sensors: ToF technology emits light pulses and measures how long it takes for them to reflect back. This helps the robot gauge the depth and size of surrounding objects. Itโs a less common technology but can be found in flagship models like the Eufy S1.
Some manufacturers take unique approaches. Samsung, for instance, uses dual cameras and what they call 3D Active Stereo on their flagship models. Narwalโs lower-end Freo X, on the other hand, relies on a โtri-laserโ system, which is essentially three infrared beams working together.
Our Updated Testing System
We recently decided it was time to update our obstacle avoidance tests. With the rapid advancements in robot vacuum technology, we felt our previous tests were no longer challenging enough. So, we revamped the tests to push these machines even further.
Previously, our tests involved running robots through a pre-mapped room where each test run featured a specific category of obstacles โ usually light and low-profile items that would challenge the robotโs ability to avoid them. The highest possible score in these tests was 12, though the average robot scored around 9. More recently, as systems improved, I began to see a few perfect scores. Thatโs when we knew it was time to create a more demanding challenge.
In our new torture test, we used the same objects but placed them all in the room at once, creating a chaotic environment. This test doesnโt just challenge the robotsโ sensors โ it also puts their navigation algorithms and processing power to the test as they work to avoid multiple objects simultaneously.
We combined the results of both tests to determine the best obstacle avoidance systems currently available.
What We Learned: The Losers
Robots that rely solely on structured light without a camera or crossed lasers have been some of the lowest scoring models that we have evaluated. At this point in time, this configuration, often found on lower-end models, just doesnโt cut it if obstacle avoidance is a priority for you.
What We Learned: The Winners
Interestingly, the top performers of our 2024 competition used a variety of obstacle avoidance methods, so it is not possible as of yet to say which type is the very best. What we did find, is that two of the top three used Time of Flight sensors, while others rely on a combination of cameras, structured light, and crossed lasers. Samsungโs unique approach with dual cameras and 3D stereo added a notable variety to the mix.
Final Thoughts
While there still isnโt a consensus on the best obstacle avoidance system, we’re getting closer to a solution every day. These technologies continue to improve, and we expect to see even more advancements in the near future.
For a little historical reference, our original AI and Obstacle Avoidance competition from 2022 is below. We expect to have a new competition available to view in the coming months.
What we test for
We wouldn’t recommend a robot vacuum just because it could avoid pet waste (although that’s an awesome feature), cords, and other unexpected objects, no matter how good it was at those tasks. A robot vacuum needs to do much more than just those.
So, while we created new tests to gauge object avoidance systems, we also incorporated a number of other key robot vacuum performance metrics, too. Those metrics included how well they cleaned on carpets and hard floors, their pickup ability with debris of various sizes, their features, as well as how owners rated them.
Results
Our final scoring involved new tests we developed that were specifically designed to test robot vacuum obstacle avoidance and AI as well as several criteria which we believe to be important to any robot vacuum.
Looking for a more basic robot vacuum? We’ve compiled our list of the Best budget robot vacuum cleaners you can buy in 2024 โ check it out!
While the Roborock S7 MaxV was the overall winner, five brands made it into the top five finishers with Dreametech, Samsung, Ecovacs, and iRobot all represented.
The Dreametech Bot Z10 Pro made an impressive showing. Not only did it capture second place, but it was also our budget choice too.
Roborock S7 MaxV: Best robot vacuum with obstacle avoidance and AI
When we factored in all the criteria for the best robot vacuum with obstacle avoidance the Roborock S7 MaxV came out on top. The S7 MaxV Ultra excelled at just about everything with one obvious shortcoming โ its price.
The S7 MaxV is available in three different packages. In each, the robot vacuum and mop itself are identical. What’s different is the docking station and its capabilities. The more sophisticated the dock, the more expensive it is.
One package includes the S7 MaxV as a standalone robot vacuum and mop and it comes with a simple charging dock. A second option, the Roborock S7 MaxV Ultra, is one of the most sophisticated docking stations on the market. Beyond charging the robot, it also empties its dustbin, washes its mopping pads, and refills the robot’s water tank.
The final variation is in between the two we’ve described and is called the S7 MaxV Plus. The Plus version’s dock charges the robot and empties its dustbin. It is priced between the other two options while closer to the Ultra.
Dreametech Bot Z10 Pro: Best obstacle avoidance robot vacuum value
When pricing was factored into the equation, the Dreametech Bot Z10 Pro was the clear winner. Unlike our overall winner, there is only one Z10 Dreametech model, the Z10 Pro. Like the middle-of-the road S7 MaxV, it both charges the robot and empties its dustbin.
Comparing the price of the two, we’ve seen the Z10 Pro sell for nearly ยฝ the price of the comparable Roborock S7 MaxV variant.
But price wasn’t why the Z10 was picked as our budget robot with obstacle avoidance. It’s because it scored well in all the tests and did so with that more approachable price tag too.
How we tested obstacle avoidance equipped robot vacuums
We mentioned earlier that we developed new tests to better evaluate robot vacuum obstacle avoidance. We created the tests based on strong points, shortcomings, and curious behavior we have observed when using robot vacuums with these systems.
All the robots we tested
In this round of testing, we included ten robot vacuums, each with obstacle avoidance and most with artificial intelligence of some kind. The ten robots were:
Robot Vacuum | Vacuum | Mop |
Dreametech Bot Z10 | Yes | Yes |
Ecovacs Deebot N8 Pro | Yes | Yes |
Ecovacs Deebot Ozmo T8 AIVI | Yes | Yes |
Ecovacs Deebot Ozmo 960 | Yes | Yes |
Ecovacs Deebot X1 Omni | Yes | Yes |
iRobot Roomba j7 | Yes | No |
Roborock S6 MaxV | Yes | Yes |
Roborock S7 MaxV | Yes | Yes |
Samsung Jet Bot AI | Yes | No |
Shark AI Vacmop | Yes | Yes |
Six Standard Objects test
This test involves six objects spaced out evenly on a hard floor. Each of the objects is something we would expect robot vacuums with obstacle avoidance to have programmed in their image library and therefore able to identify and avoid.
The objects were a few cords, novelty pet waste, a cloth, and a small toy vacuum. The test was to see how good the robotic vacuums were at not only getting stuck, but avoiding contact with the objects.
Top performers
- Roborock S7 MaxV – perfect score, tie for 1st
- Samsung Jet Bot AI – perfect score, tie for 1st
- iRobot Roomba j7 – 2nd
The Pet Waste test
In this test, the same layout was used as in the six standard objects test, but each of the six items was simulated pet waste.
Top performers
We’re providing five top performers for the pet waste test, as there was a five-way tie for first place with each robot getting a perfect score. Our fake pet waste looks pretty real โ this must be something engineers worked hard on with their AI algorithms and object library training.
- Ecovacs Deebot X1 Omni – perfect score, tie for 1st
- iRobot Roomba j7 – perfect score, tie for 1st
- Roborock S6 MaxV – perfect score, tie for 1st
- Roborock S7 MaxV – perfect score, tie for 1st
- Samsung Jet Bot AI – perfect score, tie for 1st
High performer
The Deebot X1 Omni not only did well with obstacle avoidance, it did well all around! Check out our Deebot X1 Omni review if you’re in the market for a premium robot vacuum and mop and our comparison of the S7 MaxV Ultra and Deebot X1 Omni.
The Cones test
The cones test is the same as the Pet Waste test but with cones. Once again, it is the same layout.
In the end, this test was a better reflection of how aggressive each robot was as opposed to being a great gauge of its object avoidance and artificial intelligence.
The Torture test
We also set up a seven object torture test. This test included both common objects, like shoes and socks but also objects that most likely weren’t programmed into any of the image libraries the robots used.
For this test, the pattern was also more random with some obstacles closer to others. We also included two rugs with objects placed on them. One rug was solid red with red items. The other rug had a pattern with a contrasting item placed in its center.
Top performers
There were no perfect scores in the obstacle avoidance torture test, but there was a clear first, second, and third place.
- Samsung Jet Bot AI – 1st
- Roborock S7 MaxV – 2nd
- Dreametech Bot Z10 – 3rd
The Blue-on-blue test
In this test, three different blue items were placed on a blue carpet with a complicated pattern.
This test was based on some behavior previously seen where a robot would avoid an object on hard flooring, but run into or over it on a more complicated surface such as carpet.
Top performers
In the top four finishers, there were two ties, so we have four robots below.
- iRobot Roomba j7 – perfect score, tie for 1st
- Samsung Jet Bot AI – perfect score, tie for 1st
- Ecovacs Deebot Ozmo T8 AIVI – tie for 2nd
- Roborock S7 MaxV – tie for 2nd
The Timed test
This final new test was to see how efficient each robot vacuum was. First, each robot mapped out a room without any obstacles. Next, three obstacles were added to the room. Finally, the robot was tasked with cleaning that room.
Each robot was timed to see how long it took to complete the test.
Top performers
- Ecovacs Deebot X1 Omni – tie for 1st
- Ecovacs Deebot Ozmo T8 AIVI – tie for 1st
- Dreametech Bot Z10 – 2nd
Results of obstacle avoidance tests alone
We aren’t making our final picks based solely on the obstacle avoidance tests. We also took into consideration several key aspects that make a robot vacuum a good one.
If we only look at the results from the new, obstacle avoidance-specific tests, first place would go to the Samsung Jet Bot AI, which won by a decent margin. Second place would go to the Roborock S7 MaxV. Rounding out the top three would be iRobot’s Roomba j7.
Conclusion
We’re glad we took the time and created some new ways of evaluating robot vacuums with obstacle avoidance. By incorporating other key characteristics in the best robot vacuums we think we have found a good foundation for future tests.
At the end of the day, one thing is very clear – no robot vacuum is perfect at obstacle avoidance. That might be the most important takeaway for anyone shopping for one at this time. What’s exciting is how far they have come from the first robot vacuums and how fast they are evolving.