Read the full version of this article on inorbit.ai
The market for autonomous service robots is on the verge of a massive expansion. This has been largely driven by advancements in core technologies such as computer vision as well as lower cost of key hardware components and a standardized software stack.
Like we’ve seen with other technology waves such as cloud and mobile, venture capital is pouring into the space, tripling in size from 2016 to 2017 and reaching +5B in 2017 by some estimates, which in turn is attracting more startups tackling an incredible variety of problems, from life-saving to mundane.
However there are still some big potholes on the road to widespread robot adoption. We cover 5 of them here; number 4 will not surprise you (if you are already scaling your robots).
#1 Robotics companies need to solve real business needs
The robotics companies that will succeed are those that solve a real business need. They fall in love with the problem, not with the solution.
#2 The tools that work in the lab aren’t great in the field
Once robots venture out into the real world, the tools used for development have distinct limitations.
#3 Using SSH to control your robots doesn’t scale
Moving beyond SSH could be seen as a litmus test for the maturity of a robotics company that is getting serious about operations at scale.
#4 A fleet of robots is like a data center from hell
Robots operate in uncontrolled environments, sometimes in far-flung locations, are usually mobile, have tight real-time computation constraints, connect to unreliable networks and need to be recharged.
#5 There are no best practices for managing autonomous robots at scale
The service robot industry is still evolving and has yet to develop consistent best practices. These are needed to reach the level of reliability and predictability required for massive adoption.
To learn more, about how InOrbit is addressing these needs, visit inorbit.ai or join us at RoboBusiness on September 27, 2018 in Santa Clara, CA, including our panel on Robotics Infrastructure at Global Scale.