Be among the first to streamline and optimize sensors with the Tangram Vision SDK
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For as long as Hollywood has been making films about the future, the popular imagination has been captured by visions of a world served by robots.
Yet, even though it has been almost a century since Fritz Lang’s landmark film Metropolis, we still don’t live in a world where robots and humans regularly occupy the same spaces, whether public or private. Perhaps the only exception might be my adopted hometown of San Francisco, where multiple fleets of self-driving cars roam the streets, delivery robots trundle down sidewalks delivering sushi to software engineers, and telepresence robots let remote workers (aka, everyone now) interact with others in the home office.
So, why then, is the case?
It’s true. Even though brilliant minds from the world’s best universities are tasked with building these robotic platforms, a robot is a non-trivial device to engineer. The complexity of a robot that appears simple (like a delivery robot, for instance) is, in fact, staggering. There are multiple subsystems, from control to locomotion to perception to more esoteric areas like power management and compute resource allocation. All of them need to work all of the time. All of them need to work all of the time at the same time. And if one system fails, the whole robot fails. This actually happens a lot.
Some of these systems have become hardened through the collective efforts of thousands of roboticists and robotics startups over the past couple of decades. But, for the most part, the real world is a harsh place, and it does its best to flummox a robot however it can.
Take our particular area of robotics, perception sensors. In terms of performance and reliability, the sensors available to roboticists today are leagues ahead of what was available just a few years ago. Yet these sensors can still fail for myriad reasons. Passing a poorly shielded electrical box on a delivery route can introduce EMF surges that suddenly compromise communications. A toddler might want to give a cute robot a hug, knocking a sensor off calibration in the process. Or a sudden burst of direct sunlight will exceed the dynamic range of a vision sensor, rendering it inoperable until the sun has continued its path from dawn til dusk. Or perhaps the sensors work perfectly fine, but the perception software can’t discern a flat floor from a staircase, which then gives you this:
For each failure mode, there is a solution. However, these failure modes typically don’t occur in the lab, which means that these real world failures send robotic teams back to the drawing board for what they assumed to be solved problems (or they can just use Tangram Vision to manage sensor performance during deployment).
Even with multiple rounds of venture capital and incredible development teams, we’ve seen cutting edge robotic companies die again and again because development timelines exceeded their financial runway.
As we noted above, robots can appear to be robust and reliable in laboratory environments, only to fall to pieces when confronted with real world conditions. And given the inherent complexity of robots, even getting to a completed prototype to test in a lab setting can be a monumental task.
As a result, many promising companies have had to shut down because they failed to raise enough capital to account for delays that occur during development and pilot phases.
Of course, this is one of the reasons we’re building a common integration layer for perception sensors. As we’ve spoken with dozens of robotics companies, we now understand that perception sensor integration can add anywhere from six to 18 months of unplanned time to development timelines. Six to 18 months! Delays like that kill companies, no matter what the industry. It’s as simple as that.
Videos like those showing Boston Dynamics robots performing amazing, superhuman-like feats, often serve to reinforce narratives around the dangers of releasing robots into the world. After all, what mere mortal could compete against the capabilities of robots like these, whether in work or in warfare?
For the uninformed, the idea of robot proliferation initially conjures these thoughts of job destruction. That couldn’t be further from the truth! In fact, study after study has shown that the onset of robotics and automation isn’t a job killer, but in fact is a job creator.
The most thorough study we’ve come across was done by the Brookings Institute. It concedes that robots and automation does destroy some jobs — but it then overcompensates by creating even more jobs than existed before. You can learn more here by reading their report.
Yet these studies aren’t enough. This message also needs to reach and be understood by those outside of the robotics industry. As an industry, robotics and automation still does a poor job of making the layperson understand the real impact of robots in terms of economic output and job creation.
A goal of Tangram is to help society at large better understand these benefits, and in turn, accept robotics and automation as a positive force for the world.
This may not come as a surprise. But this challenge is compounded by the fact that the newest wave of mobile robots and autonomous vehicles are operating in public spaces, and those public spaces are legislated by overlapping mandates from local, state and federal governments.
As a result, progress in one jurisdiction does not necessarily set a precedent for another. In the reverse case, statewide or federal mandates can preclude more progressive legislation at a local level. The situation for autonomous vehicle fleet deployment in California, for instance, demonstrates the complexity of managing local expectations with statewide mandates.
As an industry, robotics and autonomy companies need to work with elected officials from the local through national level to create sensible legislation that ensures public safety while simultaneously allowing for innovation that improves quality of life and economic output.
OK, truth time. I wrote this entire Medium post because this is my favorite Saturday Night Live commercial spoof of all time:
In all seriousness, the existence of this sketch is in fact evidence of society’s skepticism of robots and their safety…really! The more positive interactions that people have with robots, the sooner they’ll be accepted as productive and positive.
Robotics and automation are inevitable; all of the above challenges (even robot insurance!) will become solved problems in due time. The question is…when?
At Tangram Vision, we’re doing our part to shorten robot development timelines and increase robot reliability through more sound sensor deployment. And we’ll add our voice to our industry’s to support sensible legislation that benefits all.
Are you developing a robot or autonomous platform that uses perception sensors? Get in touch so we can see how we can help.