Looking for Perfectly Cooked Hot Dogs?
Posted: Mar 24, 2020
Looking for perfectly cooked hot dogs?
Then it's time you meet the machine learning robot's Jaco and Baxter.
It is a common conception that a swift entrance to the heart of any human is through the stomach. It has always been the priceless strategy of a fellow human to reach out to another human without even the mastery of a flirtatious social skill. Regardless of the flawed human nature, the trick always worked. What if we removed the human flaw? Not to suggest that we are tampering with the genomes of a captive human somewhere in a secret laboratory in a bid to generate a perfect human. What if a robot took the place of humankind in the kitchen? Imagine the possibility! Well, the robots are here and are busy singing the global anthem of innovation in all aspects of our lives.
Who in their right mind ever conceptualized that there would come a time where the perfect cup of coffee existed with unmatched quality and consistency. Well, if you think its a bluff, check here.
Thus the tides of a perfect coffee are ready to be a thing of the past. We should move on to the perfection of hot dogs. Firstly, we should make acquaintance with the robotic master chefs behind this ingenuity. Meet Jaco and Baxter, the machine learning robots already with distinctions in the cooking profession. If your craving is for a bite of a ballpark frank, not just any, but one with a freshly grilled taste, then you are drooling on the right article. Before we go further and anger the enzymes in our stomachs, we should take a step back and acknowledge how Jaco and Baxter came to make such incredible milestones.
It all started at Boston University, where a group of engineers who in our opinion, had the motivation to automate their lunch breaks. Let's say to avoid unnecessary planning in regards to what and where to eat. A technical brief of their profiles narrates that they are meeting milestones in machine learning. Thus they are convincing robots through technical tutorials to perform and complete complex tasks. Such a framework is the wildcard in identifying a host of mammoth tasks. It is like trying to crack the code of free will for the robots so that they can think for themselves and act for themselves in accordance to set rules and guidelines. Think of it this way, the war on cancer will no longer be like fighting a cunning alien species. It will be easy for the robots to identify and manage the cancerous spots through mammograms. Moreover, their understanding and mastery of spoken commands will empower them in fields like music where the robots can replay your perfect piano tune.
Before we carry ourselves too much ahead in our imagination, this article is about Jaco and Baxter and their conquest in the preparation of the perfectly cooked hot dogs. The imaginary future of their extended family will come to pass when it is time. Let's dive into the proof of concept and try to understand how robots are preparing hot dogs. Researchers are still scratching their heads over the thoughts of machine-learning algorithms. They do not fully understand its practical approach, that is, the learning bit. Thus even though it is practical, it is human nature to be cautious. Hence the reluctance by engineers to risk the applicability of this concept to complex and high-risk tasks. Thus applications that prioritize human safety such as autonomous driving tend to be an applicable challenge.
The BU College of Engineering professor, Calin Belta, in a Science Robotics publication together with the contribution of his lab’s researchers brought the cutlery skills of Jaco and Bexter to life. The two robots learned the cooking, assembling, and serving process entailing hot dogs. The combined methodologies in play were from the techniques of formal methods and machine learning. The formal method is a subset of computer science whose typical application approach is towards the guarantee of safety. Its notable use is in the fields of Cybersecurity software or avionics. The dispatch of these techniques is indeed rocket science. Thus combining the concepts and coming up with an understandable robotic language is not an easy task hence requires skill and precision to avoid application catastrophes.
Through the knowledge of his profession in Mechanical, Systems, Electrical, and Computing Engineering, professor Belta, with the aid of his team, came up with a plan. They employed reinforcement learning, which is a branch of machine learning. In summary, a computer gets a task to accomplish. If the task is complete with a success factor, a reward is availed, which acts as a guide to its learning process. The steps needed to accomplish such a task have an outline on an algorithm notable as ‘prior knowledge’. The algorithm does not, however, outline the walkthrough or execution process of the laid out steps. The robots thus have to improve on its performance delivery approach, and if auspicious each time, its rewards continuously increase. The approach resultantly leads to the creation of a feedback mechanism. Thus the robot is pushed to embrace a better learning approach of better executing the laid out tasks. In this example, the milestone to conquer will be how best or I which position a hot dog should be on a bun.
Thus it is safe to state that the integration between formal methods and reinforcement learning under prior knowledge is the reason behind the novelty of this technique. The combination of the stated three techniques is a sure way of accomplishing incredible milestones in the robotic industry. Moreover, such a team can reduce the possible runs a robot needs to take to perfect a task. In this case, it is the robot’s ability to safely cook, assemble, and serve the hot dogs simultaneously. Professor Belta acknowledges this work as a proof with a workable concept. It is a demonstration of a generalized idea under execution. Thus moving forward, he hopes that the knowledge and data from this working concept are enough to trigger a milestone on other complex tasks. A common item on this bucket list is autonomous driving.
The Jaco and Baxter robots are just a pioneer of the many future robotic accomplishes. To the humans, the sky might be the limit, but to robots, it is the conceptualization of machine learning.
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