A few months ago, as part of preparing to present Sawppy to the Robotics Society of Southern California, I described a few of the challenges involved in putting ROS on my Sawppy rover. That was just the tip of the iceberg and I’ve been thinking and researching in this problem area on-and-off over the past few months.
Today I see two divergent paths ahead for a ROS-powered rover.
I can take the traditional route, where I work to upgrade Sawppy components to meet expectations from existing ROS libraries. It means spending a lot of money on hardware upgrades:
- Wheel motors that can deliver good odometry data.
- Laser distance scanners faster and more capable than one salvaged from a Neato vacuum.
- Depth camera with better capabilities than a first generation Kinect
This conforms to a lot of what I see in robotics hardware evolution: more accuracy, more precision, an endless pursuit of perfection. I can’t deny the appeal of having better hardware, but it comes at a steeply rising cost. As anyone dealing with precision machinery or machining knows, physical accuracy costs money: how far can you afford to go? My budget is quite limited.
I find more appeal in pursuing the nonconformist route: instead of spending ever more money on precision hardware, make the software smarter to deal with imperfect mechanicals. Computing power today is astonishingly cheap compared to what they cost only a few years ago. We can add more software smarts for far less money than buying better hardware, making upgrades far more affordable. It is also less wasteful: retired software are just bits, while retired hardware gather dust sitting there reminding us of past spending.
And we know there’s nothing fundamentally wrong with looking for a smarter approach, because we have real world examples in our everyday life. Autonomous vehicle research brag about sub-centimeter accuracy in their 3D LIDAR… but I can drive around my neighborhood without knowing the number of centimeters from one curb to another. A lot of ROS navigation is built on an occupancy grid data structure, but again I don’t need a centimeter-aligned grid of my home in order to make my way to a snack in the kitchen. We might not yet understand how it could be done with a robot, but we know the tasks are possible without the precision and accuracy demanded by certain factions of robotics research.
This is the path less traveled by, and trying to make less capable hardware function using smarter software would definitely have their moments of frustration. However, the less beaten path is always a good place to go looking for something interesting and different. I’m optimistic there will be rewarding moments to balance out those moments of frustration. Let’s learn to love imperfect robots just the way they are, and give them the intelligence to work with what they have.