What is the biggest gap in robotics research?

There are two major gaps that we should at least investigate as part of the process of defining robotics as a discipline.

1.     We don’t have positive laws.  Our history is still largely trial and error and scavenging from other disciplines, rather than the development of foundational design principles or laws governing the creation or operation of robots in general.

We do have recognizable (tongue-in-cheek) negative laws, roughly equivalent to Murphy’s Law.

The First Law of Robotics:  You’re wrong (you set the parameters wrong, the user doesn’t need the robot to do whatever it was you thought they wanted, your model of the environment was wrong, etc.);

Another Brick From The (Research) Wall

In every research project, you eventually run into a wall.  The wall can take many specific forms, but in general it represents a point at which it seems like your idea can’t work.  There are at least four possible responses.

First, you can walk away.  You can abandon your approach to the problem, backtrack until you find an alternate path, and follow that path to its wall.


Electrical engineers have nice definitions for the foundations of their field:

We can define

and so forth.  But in robotics every term is subject to change without notice.  There is no common definition of robot, or autonomy, or intelligence.  The only common element is that researchers are still, after three or four decades, able to argue about what the definitions ought to be.

The Core of Robotics

What is the core of Robotics as a discipline?

You could argue that robotics is an engineering discipline, because we work on the design, building and use of robots.

You could also argue that robotics ought to be more a science than an engineering discipline alone, since we provide new kinds of tools and models for other disciplines in much the same way mathematics does (with the admittedly large difference that our tools exist as physical objects).

Or you could argue that mathematics and robotics lie on either side of engineering, with mathematics providing the inputs to engineering and science and robotics coming out the other end as the ultimate synthesis of engineering and scientific fields.

A Few Thoughts on “Killer Robots”

I’ve been following the discussion over on IEEE Automaton about the letter from the AI conference in Brazil, (for, against, rebuttal, etc.) , and since this is the kind of thing that normally gets me very engaged (or enraged), I was surprised to find myself ambivalent on the subject.

The original letter ends, “Starting a military AI arms race is a bad idea, and should be prevented by a ban on offensive autonomous weapons beyond meaningful human control.”  but this gives us several propositions to consider:

  • “Starting a military AI arms race is a bad idea”

Are “Animal Robots” Robots At All?

IEEE Spectrum had an article from a Chinese lab on “animal robots”. When I was back in grad school, we worked on a proposal for a similar project. We were going to connect moth antennae to a robot and use them as sensors to drive the robot around. Various people have worked on similar ideas over the years, and they’re a little disturbing but generally very informative.

This paper had a diametrically opposed approach. Instead of replacing the animal’s actuators with a robotic interface, they mounted a controller on the back of a rat and connected it to the rat’s motor neurons. Instead of creating a robot with biological sensors, they created a remote control animal.

Enough Inappropriate Ethical Analysis Already!

I’ve reached my threshold for uninformed articles about the supposed ethical conundrums that roboticists should be taking into account when they design autonomous cars.  At the end, I’ll be adding more questions to the list of potential research topics, but first, I want to address why these articles are so infuriating.

Grrrr.  Begin rant.

The articles don’t seem to have been vetted at all.  Exhortations to follow Asmiov’s three laws, or (worse yet) implement additional laws and address philosophical dilemmas about which group of people to kill in some avoidable concatenation of tragic events – they all incorporate assumptions about how robots are built and designed that are (at least currently) untrue.

Robotics Also Needs Historians

What would enable to faster progress in robotics research?

Part 2:  Historians

One of the other things that would help us progress faster is a better understanding of what ideas have already been tried.

Trite, I know, and readily apparent, and something that applies across most (all?) scientific domains.  We’re not an established field like Biology or Chemistry, and we’re effectively still at the very beginning of defining the laws and principles that will be our foundations.  If we don’t know what approaches have been tried and failed, and have some sense of why, we won’t be able to define those laws and principles.

Robotics Needs Librarians

What would enable faster progress in robotics research?

Part 1:  Librarians.

There are several answers to this question, but one of the most important things robotics needs is the ability to find existing solutions, and one key element of that is providing cataloging tools.

Every robot is built up of bits and pieces of other peoples’ algorithms.

The researchers focused on a given problem know what the state of the art in that area is.  But each robot is an assemblage of components – no matter which piece a given researcher is focused on, the rest of the robot must be present in order for that piece to be tested.  Unfortunately, no one researcher has time to be an expert in every component of a robot.

First Question … Nomenclature

What should our discipline be called? Should it be called Robotics Science, or Robotics Engineering, or neither? Why?

Neither. It should be called Robotics.

We don’t say “Chemistry Engineering” or “Physics Science”.  Robotics is not Robotics Engineering or Robotics Science.  But the problem isn’t really one of nomenclature.  The real problem is that Robotics doesn’t fit smoothly into these categories.

We could acknowledge the existing separations in the discipline between the hardware-centric researchers in Mechanical Engineering and the more theoretically oriented Computer Science groups, but the process that seems to be occurring is one of merging rather than separation.