Ultimately, process models are there to keep robots on task and limit the need to optimize them whenever a new surprise comes up. Ultimately, circumstances where the human eye may not be entirely reliable could prove exceedingly efficient with autonomous robots. In these circumstances, robots that can respond to different shapes, orientations, tasks and recognizable objects can do so in a hierarchical fashion, meaning it can address increased complexity without a concomitant increase in processing complexity. While a certain predictability is still required for them to function, we know that certain edge cases or tasks may be even more complex. In fact, it is mostly what autonomous robots must be used for. In this circumstance, the architecture of a robot’s processing capabilities must be adapted to account for the possibility of unexpected inputs, however this doesn’t mean that responding to those inputs is impossible. Whether it’s visual, auditory or data connected to the robot from the environment around them (hello, IoT), there is potential for unexpected surges of data to occur within the framework of whatever a robot can functionally interpret. With the process models and behavioral frameworks used by autonomous robots, various kinds of sensory data can be accounted for. While advances in neuroscience are coming fast and furious, you can probably rest assured that your autonomous robots will still need some everlasting guidance within your lifetime and far beyond. While it’s conceivable that an engineer or scientist could attempt to build this sort of consciousness, we don’t even understand how this consciousness works in humans – so how would it be possible to then replicate it in robots? Ultimately, robots need goals set for them, which disregards the “AI super predator” dystopian future scenario almost entirely. Whether a divine hand was involved is another story entirely, but when we think about the “evolution” of autonomous robots certainly hasn’t been guided by gods, but at the same time, they simply haven’t been built to think abstractly about their own goals and motivations. We’re not philosophers, but the ability of humans to dream up objectives, set goals or even invent ideologies is usually considered as a consequence of evolution or our own sensory mechanisms. With autonomy robots will begin appearing in more everyday environments – as well as in more places within those manufacturing, logistics and research facilities! This is possible because autonomous robots generally have the ability to perceive their environment and use pre-developed strategies to “program” themselves towards a goal, while taking into account obstacles, safety concerns and their own constraints (everything from joint rotations to battery power).īecause of this level of flexibility, manufacturers with highly varied applications, warehouses that serve a variety of consumer needs and service businesses that require deliveries or transportation out on busy and unpredictable streets will all benefit from a new wave of robotic autonomy. This simply hasn’t been useful outside of mass manufacturing, logistics and research facilities. Why is this the case? Traditional robots require extensive planning, programming and fixed environments to ensure that everything can be done as predictably as possible. Autonomous robots serve the same function, but in a broader array of circumstances. Robots have always been best suited to helping with repeatable tasks. As in all things AI, autonomous robots can cause our imaginations to run away with us, but with the right references, we can bring things a little more down to earth (and explore the practical benefits)! If you’re thinking about how to contextualize autonomous robots in your own work environment, here are a few CANs and CANTs to guide you. While people can be more picky in the roles they choose to perform, robots are even more necessary to execute the basic jobs upon which our economy and high standards of living depend. The world is going through a first-of-its-kind “demographic inversion” which actually limits the availability of labor for a variety of traditionally human-led jobs. This is particularly important because, as it happens, skilled labor is in ever shorter supply. These new capabilities – whether it’s in remote inspection, materials handling, delivery services or manufacturing processes – all enable robots to limit the need for humans to execute dangerous, dull, and sometimes even deadly tasks. New forms of walking, lifting and rolling robots as well as improvements to traditional industrial robots all make these systems more flexible and adaptable – particularly in unstructured environments. Autonomous robots can perform varied tasks in a flexible, responsive manner with limited human oversight.
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