Robotic Dexterity

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Robot Dexterity

Posted by Rahul Kumar on

  • What does it mean when a robot is described as "dexterous." And what does it mean for robot users? Here's what to look for when you're selecting a robot based on its dexterity.
  • The word "dexterity" is thrown around a lot in the robotics world. It's used by robot manufacturers who describe their robots as dexterous. It's used by robotics researchers who describe the dexterity of their developments. It's used by gripper manufacturers who describe their grippers as dexterous. You might ask: How much dexterity does my robot need to have? The answer: It's impossible to say. Nobody can seem to decide what makes a robot dexterous. Robotic dexterity is a complex topic. It's hard to tell how much dexterity you'll need for a particular robotic application — or even if "how much" is the right question to be asking.
  • To understand why this is a tricky topic, it's useful to look at an example. Last year, a research team from UC Berkeley claimed that they had created the "most dexterous robot ever created". When I heard the news, I was skeptical. Not because I doubted that they had made a technological breakthrough. I was skeptical of the word "dexterous". I knew from experience that this word is a moving goalpost in the world of robotics. You see, I investigated robot dexterity as part of my PhD, which I completed back in 2014. During my research, I discovered that there is no standard definition for "dexterity" in the robotics community. As a result, researchers often claim that their robot is "dexterous" without defining what this means. This makes it very difficult for robot users. If we don't know how dexterous a robot is, how can we tell if it's the right one for our task? I was right to be skeptical. The UC Berkley team had done what many researchers have done in the past. They had invented an entirely new metric to measure dexterity. Their metric ignored the physical properties of the robot and instead focused on machine learning performance. There's nothing inherently wrong with their new metric — which is really a measure of bin picking speed — but it certainly can't be used to prove that the researcher's robot is "the most dexterous robot ever created." In order to say that, you'd need to measure all dexterous robots using the same metric. This is not an isolated case. I've seen the same thing happen again and again. People use their own definition to try to prove a robotic system is dexterous. There is no standard metric for dexterity — not until ISO nails it down at least. Unfortunately, that means you have to find your own way to assess a robot's suitability for your task.
  • Here are some of the important factors which relate to robot dexterity, along with questions that you can ask yourself to narrow down the needs for your task: Object size — How small are the objects that the robot will manipulate? Are there a variety of sizes or are all objects identical? How does this compare with the reach required of the robot? Object shape — What shape are the objects? Do they have many complex edges or a simple geometrical shape? Are they spherical or otherwise difficult to grasp? Gripping strategy — What are the different ways that the objects can be grasped (e.g. with an encompassing grip, internal grip, or suction)? Are there different ways to grasp the same objects? Are the objects delicate and so require a particular gripping strategy? Reachability — How much does the robot have to "stretch" to reach all important locations in the workspace? Does it need to use all the robot's workspace, or just a small part of it? Does it need to approach locations from many different angles? Speed — What cycle time is required for each action?