Robotic Companions of the Future

Many articles that focus on the increasing similarities between organic life and machines focus purely on the ways that humans are becoming increasingly mechanized. It can be assumed that people will become even more like machines as the collective human consciousness moves towards a single technological singularity. However, what might be more startling is the way in which machines are often beginning to resemble other animals aside from humans.

Few singularity concepts comment on what could happen to animals when the next level of human development occurs. Individuals connected with Boston Dynamics have been working on a class of robot that might function as pack mules in the near future (example above). Rough areas are typically unkind towards wheeled vehicles however the good folks at Boston Dynamics are working on some rather cutting-edge stuff that might just solve this issue.  The project is funded by the Defense Advanced Research Projects Agency (DARPA), which hopes the robots might serve a military purpose in the future. They could easily carry military equipment through tough terrain.

The machines are powered by a go-kart engine and feature a ruggedized onboard Pentium 4. Computers onboard the robotic craft run a commercial Unix distribution called QNX. Interestingly enough, this sort of hardware and software is readily available to many consumers. Such experiments are, however, usually best left to the big boys. I’d personally love nothing more than to build a miniature version if I ever had the funds to do so.

Few singularity concepts mention animal life, and it can be difficult to suggest that nature itself would ever need to be altered. In fact, such things could be criticized as immoral. However, this technology proves that the best natural ideas can be improved on via mechanical engineering and ingenuity. The Big Dogs, as they’re called, could be the robotic companions of the future as well as the military designs of tomorrow.

Image Credit: Boston Dynamics

Additional Learning Resources:

 

Post Navigation