Lab Automation


for short. While similar in appearance to tradition- al industrial robots, a cobot is designed to work alongside humans in a collaborative but controlled work environment. These cobots can sense the presence of a person, adjust their movement speed accordingly, have specially-designed joints for impact reduction, and an exterior design minimis- ing sharp corners and pinch points. They have advanced additional sensing for better understand- ing their environment and are able to be readily- taught through simple interactive steps. They do not require guarding, and can be positioned along- side human workers in a wide range of settings. Several technology advances have enabled cobots to progress in their development. Notably, torque and force sensing has advanced to the point where a cobot ‘feels’ the impact with an object or person, and is able to shut its motion down and absorb the force of impact while only delivering a very modest amount of force to the object or person. In addi- tion, ranged motion sensors allow cobots to know if someone is moving into their vicinity and adjust their speeds accordingly. As sensors and electronics generally have become more sophisticated and far less expensive, robots have been developed with numerous safety and sensing redundancies, turning the traditional unintelligent, non-sensing industrial robot into a somewhat intelligent mechanism capa- ble of operating in the same workspace as people without posing a danger. These technologies have allowed the cobots some key performance attributes, such as power and force limiting and speed and separation monitoring4.


The development of cobots is, in many ways, driving the overall societal discussion about robots and jobs which, while having a legitimate basis in fact, is also at the peak of its hype cycle. From our vantage point, we do not see robots replacing any- thing close to 50% of jobs in any timeframe worth discussing5. Books such as Rise of the Robots by Martin Ford and The Second Machine Age by Brynjolfsson and McAfee offer directionally cor- rect views on how robots will accelerate their pen- etration into labour markets, but likely overstate the pace and extent to which it will happen. In addition, robots will not design, programme or maintain themselves for a long time, allowing job creation alongside job elimination. Still, penetra- tion of automation will accelerate and cobots are one of the most important drivers. Why? The advent of a robot capable of operating in a workspace alongside humans greatly widens the number of jobs that can be automated. Inherently safe robotic arms combined with advances in sens- ing (is a person present, am I hitting something or


Drug Discovery World Fall 2017


can I use the arm to measure something, am I picking up a cat or a gear?) and machine learn- ing are creating an explosion of appli- cability. By allowing robots and humans to share tasks, the robot technology bar is ironically low- ered significantly, allowing a much more frequent case of incremental advancement and deployment. Most estimates suggest that less than 10% of jobs are fully automatable6. Cobots answer this problem by allow- ing less than 100% robotic solutions. Warehouse auto- mation is a good example of human and robot collabora- tion lowering the robot technology bar. In a typi- cal warehouse operation, humans spend roughly 50% of their time walk- ing from one location to another7. They receive instructions about an item to pick from stock, walk to its location, put it on a cart and walk it back over to a packing/shipping station. Rinse, repeat. Using existing sensing tech- nology, indoor navigation and mapping methods and a small robotic mobile base, a fairly inexpen- sive robot can be designed to replace the walking portion of the overall warehouse picking task. Numerous examples of such robots are currently being developed by companies such as Locus Robotics, Gray Orange, 6 River Systems, Fetch Robotics and others. On the other hand, asking a robot to reach into a bin and retrieve a wide range of objects is very complicated. As the work at the University of California Berkeley on teaching a robot to fold laundry8 has shown, a robotic system with sufficient machine vision and gripping tech- nology to pull a single object out of a location accurately is a challenge (Amazon has an annual contest on this problem9). Even if possible, a vision-based robot picker is much more expensive than a robot only designed to replace the walking in the picking task. Human eyes and hands will be the best picking technology for a long time to come. Thus, by having humans pick items and pass them to robots, the vast majority of the labour cost can be reduced without taking humans completely out of the equation. This is how collaborative robots are opening up new applications and mak- ing stepwise advancement possible. As only about


Colab silhouetted arm


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