Here at Singularity Hub, we are interested in the different types of robots capable of doing a normal person’s job. We have discussed Honda’s Asimo (who replaces the average butler) and recently talked about KIVA Systems’ warehouse robot (which makes redundant all members of the Storage Rack Lifters Union). In case you were worried about the KIVA feeling alone (why not worry about those unemployed storage rack lifters instead?), worry not. The KIVA no longer needs to be lonely while toiling away at the warehouse. Meet its new friend: the Autonomous Forklift.
The autonomous forklift, currently being developed by students and faculty of the Massachusetts Institute of Technology (Singularity Hub regulars known for the robot gardener and sixth sense) in conjunction with Draper and Lincoln Laboratories, promises to bring a new wave of futuristic technology to today’s warehouses. This is not your average Roomba with tines stuck on the front; it is designed from the ground up in order to work with humans in a human world. The forklift is able to sense its surroundings and make decisions accordingly, combining agility with intelligence and allowing it to act in a constantly changing environment.
Most robots up until now are programmed to do a certain repetitive task and, with no human interaction to make a mess of things, are then left to do the work. This forklift, however, is being designed to move pallets for the military in a variable environment where humans work and interact with the machine as coworkers. Its programming makes it responsive to voice commands given by workers within the warehouse, allowing easy integration into any building with any staff. And if the job is just too tough for the current firmware to figure out, there is always the option to revert to good old manual labor, wherein a person can jump in the driver’s seat and take the controls.
Funding for the forklift is coming from the military, with hopes that it will eventually see the light of day in military storehouses before making its way out into the civilian world. The project, however, is still in its developmental phase and is not likely to hit the military base for quite some time. It is currently able to sense and engage pallets but the aforementioned intuition and decision-making has not yet shown through. Take a look at the video below for an active demonstration:
This forklift not only represents a further synergy between man and machine, but it also is an interesting step forward in the field of robotic coding. The code for this heavy lifter was initially written for use in a DARPA Grand Challenge Vehicle and only slightly modified for this application. Code recycling in this manner is a growing trend within the robotics community and may stand as a stepping stone for a future standardized autonomous vehicle code, allowing for even more rapid creation of advanced robots aimed at doing any multitude of jobs.
Such a standard could open up the doors to converting everything and anything into an autonomous robot, eventually making many manual labor tasks obsolete. Fans of Marshall Brain or those worried about robots causing widespread unemployment, fear not. These autonomous workers are not out to steal all of our jobs (not yet, at least). Despite being able to operate safely and without fatigue, they still require people to watch over them and tell them what to do.
As the dissemination of the autonomous robot into factories and warehouses proceeds, manual labor jobs will inevitably be lost. However, there is no clear indication that, in the near future, robots will be able to carry out jobs that rely less on brawn and more on brains, meaning that manual laborers would need to be retrained in other fields. This will augment the continuing trend of a service based economy, where jobs in production are dwindling while jobs rooted in human intelligence continue to grow. For the moment then, it looks as if these brain-intensive jobs are safe from a robotic takeover. Yet if research in artificial intelligence suddenly takes off, perhaps we all may be scouring the classified section.