Consumer robotics is a fascinating, and largely accessible, aspect of a smart(er) home. The nice thing about consumer robotic devices is that they take chores that few of us look forward to or cherish and pass them onto machines that (until Skynet becomes self-aware) simply don’t care about losing an hour or two on what we could consider to be a precious weekend afternoon. As it becomes easier to build robotic prototypes, we might see them pop up in more aspects of our life. 

iRobot’s Roomba vacuum cleaner, the Maytronics Group’s Dolphin Robotic Pool Cleaners, and John Deere’s Tango E5 lawnmower are examples of how robotic technologies exist in, or are beginning to enter into, our lives and relieve us of the tiresome chores that cut into our leisure time. Think about the time you spend vacuuming and mowing the lawn: at what point, in your estimation, do these technologies pay for themselves? Depending how much you dislike the chore, or how much time (or money) you spend on the chore, you might feel as though the investment quickly pays for itself.

Then there is Google’s Driverless Car. Relative to the time we lose commuting, the time we waste mowing the lawn is nothing. On average, we spend about 50 minutes each day driving to and from work; and worse around major cities (take a look at this great / wildly depressing data visualization if you would like to see how your commute stacks up against those of your fellow). The potential of automated cars (be they made by Google, established car manufacturers, or a 19-year-old science fair winner) to return time to us is remarkable, provided that they are not hamstrung by legislation, regulation, or the lobbying efforts of existing industries that are more comfortable with incremental change (Joann Muller did a nice job of covering this aspect of the challenge over at Forbes with “Silicon Valley vs. Detroit: The Battle For The Car Of The Future“).

Exciting things happen when these technologies take advantage of and contribute to data that is effectively a public good. Microsoft Research, for example, has done some really interesting work in using machine learning to find the fastest route to a destination based on historical data. If you couple this analysis with an automated vehicle, we might be able to recoup more of our time and apply it to more productive or enjoyable pursuits (provided we could get over the all-too-human reaction of wondering why we are being taking a certain route when we know that another route is faster).

Beyond the vehicle, consumer-facing robotics begins to get a little trippy, if not gimmicky. There was the video from Domino’s looking at how pizza could be delivered by quadcopter and the more…whimsical Burrito Bomber concept from Darwin Aerospace. In reality, provided batteries get smaller and lighter and engines more powerful (without getting larger and heavier), the automated delivery of products is not inconceivable. It will just be a matter of economics.

This trend toward prototyping and manufacturing automated and robotic products could accelerate given the the popularity of things like Lego Mindstorms, the Raspberry Pi, and the Arduino platform (and the huge number of sensors and other components made for it).

Consumer-oriented robotics also are likely introduce some new dynamics into different corners of the consumer space: while the cost-benefit analysis of deciding to buy or lease a car (or a dwelling) is fairly well known, what happens when technologies are changing rapidly enough to make items that historically were considered durable goods less…durable? This dynamic is not likely to apply to service-based automatons like Domino’s notional pizza delivery system. It might, however, cause us to think differently about our relationship with our lawnmower if that lawn mower costs $2,000. Software updates like the ones for GPS systems could mitigate some of the risk associated with a purchase, but they might not be wholly satisfactory when the platform itself is still experiencing substantial structural changes.