Do socially animated robots just waste energy?

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So today I stumbled across this IEEE spectrum post on Care-o-bot, mark 4. I hadn’t actually come across the previous iterations of Care-o-bots, but I must say, looking at the video of the first attempt, I doubt there is much to be missing out on. Sorry Fraunhofer…

There is a link to a rather fun little promotional video of the robot, and as I watched it, I certainly felt a light hearted joy. The music was upbeat and gently fun, the basic unfolding of the plot was touching, and there is great attention to detail in the animation of the robot. HRI lessons have been picked up well here.

The robot design is simple at the heart. Slick white paint, some LEDs to provide robot specific feedback channels, and two simple dots for eyes. There is a whole host of research from HRI that demonstrates that simple is very effective, when used properly.

I particularly liked the arm movements when the robot is rushing around to get the rose. It certainly helps us empathize with the robot, no questions there. However, there is a price to pay for this. Battery cell technology is certainly coming along, but for robots energy is still a very precious resource.

So, my question, and it’s a philosophical one, and depends on how much you buy into the H in HRI, and of course what function the robot serves. Those rushing around arm movements that clearly conveyed a robot rushing around to achieve a goal. And in turn, given that, you might infer that the goal has quite some importance. They probably required a fair bit of power. Where they value for watts? Was it worth expending all that energy for the robot to rush around? Did they really bring that something truly extra to the robot?

I don’t think that there is a right or a wrong answer, but I think that this does remind us that from a practical perspective (at least for now), energy is precious to robots, and we as robot designers must contemplate whether we are using it most effectively.

Happy musings!


IET Talk on Dyson 360 eye

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Here’s an interesting video from an IET event held in Bristol in early October. Mike Aldered talks through the story and development behind the 360 eye, and highlights lots of interesting things surrounding the development of robots from a company perspective.

Mike does a great job does illustrating some of the differences in the conceptual problems that academia addresses, and the real challenges faced when applying some of the solutions to real-world problems. Makes me want to point to my last post again. Ask yourself how can you apply your research to the real world? It is worth thinking about!

Watch the video here.

Moving to Dyson, and thoughts on academic research and industry

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So, it’s been about 10 weeks since I joined Dyson (makers of the 360 eye robot vacuum), having left Engineered Arts over the summer, and while the move itself was perhaps not the most opportune thing to happen at that particular point in time, I think that it has been a very good outcome in the grand scheme of things. I’m back in Research, which, after a stint in a pure development role, I now realize is where my heart is. Also, I’m in job where I can apply more of my broad skills set. Generally, I’d say that I’m happier with the direction of my life and career.

It has been about a year since I decided to move out of academia into industry, and while it has been a bit of a rollercoaster ride, I’ve had lots of experiences and insights that been good food for thought and reflection. Though my time at EA was short, and rather stressful at times, I learnt some very important things about the differences in the internal functioning of small (and now larger) companies and universities, as well as the differences between robotics development, and robotics research.

Running a small company is clearly very difficult, and I take my hat off to anyone who has the guts and endurance to give it a sustained go. I don’t think that I have those guts (at least not now). Also, in a small company resources are stretched and managing those resources is difficult, and when you are a resource, that can be a very rocky journey indeed. That is something that I didn’t really get in academia, so it was quite a learning curve to get used to that.

I think that one of the most important things that I learnt in EA was to do with software development/management. I always suspected that software development in a PhD environment followed some “bad practices”, and when I look back at how I was managing software during my PhD (it was all via Dropbox, with no version control!) I was lucky nothing messed up too badly. What I saw in EA was something that was far more extreme than anything else that I had seen previously and it was a big eye opener. I also paid a lot attention to the style of (python) coding that I saw at EA as I was working with a couple of professional and very experienced software developers. Needless to say, I learnt a lot about software development in my time there.

Dyson is a completely different kettle of fish. For a start, it is a much larger company compared to EA, but still a small fish in a big ocean. Also, it is quite widely known that it is a very secretive company, and as such, I can’t say much about it. However, that is part of what makes it such an exciting place to work, and also very different to the academic environment. This secrecy is a strange thing coming from academia, which traditionally is very open. It takes a little getting used to, but it a very important aspect of the company (again, I can’t say much about work).

Overall, I’m quite glad that I made the change to industry, as I’ve learnt alot, and I think that I have become a better engineer, and a better roboticist as a result, which is generally my goal. I’m also happy to be working with robots that are truly going into the “wild”, as I feel that I am closer to helping make robots make a meaningful impact to the world – I can see the fruits of my labour in the hands of real people/users. That gives me alot of job satisfaction.

I’ve always had an uneasy feeling that there is a disconnect between academic robotics research and the trajectory that it is trying to depict/push – this “all singing and dancing” robot that is inevitably coming – and how we are actually going to get there given the current state of the (social) robotics industry and the current trajectory. I strongly believe that we need the population to get used to idea of sharing the world around us (physical and perhaps cyber space) with autonomous robots ASAP, before we unveil these “all singing and dancing” robots.

From what I have seen, it think that this is vital in order to promote uptake of smarter future robots (the kind that academia is has in mind) – if we are uneasy with robots around us, we will never accept these future robots (particularly as they will be larger in general). With that, I generally feel that there is a lack of academic HRI research that addresses research issues that will impact (and help) industry in the next 5 years or so. This is the kind of time frame that will help companies move toward building robots that academia is aiming for. Make no mistake, companies like Aldebaran, Dyson, iRobot, Samsung, Honda, EA, ect, are at the forefront and cutting edge of manipulating the uptake and wide-scale perception of robots in the present, and they are holding the steering wheel that will direct the trajectory of the kinds of robots we will see in the future (based upon how people react now, not in 10 years time).

I guess that there is perhaps a little message in all of this – if you’re an academic, and asked me for a research advice, I’d encourage you to tackle practical issues and provide solutions that companies can pick up and run with in a fairly short time frame. The alternative to this is work that stays “hot and alive” in a research lab, but has far less utility outside the lab space. In essence it could be collecting dust until a industry is in a position to actually apply it (if it remembers and/or finds that the work was ever done).

I’m stopping here, as I’m not sure whether I’m drifting off topic from what I had in my head when I started writing this post. I do think that it captures some of my thoughts on academic research and how it applies to industry. I’ll probably mull it over a bit more, and dump my thoughts here at a later date as this is a topic I have been thinking about for a while. However, if you have an opinion on this, I’d love to hear it! Perhaps it’s a topic for the HRI conference panel?