A bit shocked to realise how I'd completely forgotten about robotics whereas it had seemed the grandest challenge. Is robotics itself slipping toward being marginal as physical manipulation is becoming less important over time? The sci-fi robots don't even walk these days, they're holograms etc. I'm not a software engineer so it's not just that
Open Problems in Robotics
81–90 of 232 posts
Re: Open Problems in Robotics
#82Earlier quoted context omitted.
This is the scariest part of using machine learning as an engineer on any practical application as well. Without an error bound, ML can’t be in charge of anything that could put human lives at risk. This is also why I don’t understand all the hype about FSD / L5 autonomous driving. We don’t even know yet if such error bounds even exist, so we don’t even know if machine learning is even the right tool for FSD yet. All…
What do you think the error bounds are for a human? I know it sounds like a flippant question, but for certain applications, if we can get a model that's better than human, then it doesn't need to be perfect. And they way we currently do this in all sorts of ways is to pair a human with a computer so that they each do what they're best at. It doesn't have to be about full automation.
Human is like your ancient software that was here since forever and somewhat worked fine. So everyone is used to it.
(the difference from an actual software is that humans are based on some crazy nanotech from the future that nobody can completely control)
Re: Open Problems in Robotics
#83Earlier quoted context omitted.
If you have a vision system that "just works" and produces high-quality pointclouds in an actual kitchen environment, with reflective appliances, silverware, shiny countertops, shiny ceramic dishware, and glasses, we would absolutely use it. We have in-house research work on both learned monocular depth (so-so for robotics tasks) and learned stereo disparity (much more promising), so progress here isn't impossible, b…
Hypothetically, it seems that your problem has to do surfaces being reflective in the visible light spectrum. Do you have any luck with ultrasonic, ultraviolet, or IR sensors? Also I was also thinking about how light source estimation might be viable work around for reflective surfaces. http://www.thomaswhelan.ie/Whelan16ijrr.pdf
Near-IR, which many of the available ToF (Kinect2, K4A, Basler/Lucid/Sony), active stereo (Realsense D4xx, Mynt, plenty more), and many some structured light (all Primesense derivatives, some older Realsense) cameras use, as well as close UV frequencies, suffers much the same issues as visible light. Farther wavelengths in shortwave IR start to have different/better properties, but the costs of cameras are just astronomical (~$20K/camera). Farther UV is also possible, but eventually we're dealing with frequencies that are actually harmful.
I do think there's a lot of open possibility in using more than the traditional visible spectrum. Using polarized sensors to remove reflections, or hyperspectral cameras to reduce noise that only appears in certain bands are good ideas. The problem is that we've got lots of cheap imagers that are really well built for visible spectra, and not a lot outside that. Small hyperspectral cameras for things like agricultural drones do exist, but they tend to work by combining multiple sensors (one for each band) which works fine for the ranges a drone operates at but not very useful at the close range indoor robots need.
Ultrasonic has a rather bad name in the field, a lot of people having used absolutely terrible robots with basically useless ultrasonic rangefinders early in their careers. In theory sound could be really useful, and there are some very nice (and very expensive) imaging sonars for underwater robotics use, but I'm not aware of any high-resolution ultrasonic sensors for land robots. One minor challenge with ultrasonic sensors in real products is ensuring that they are inaudible to people and pets - when they are almost-audible they are extremely annoying or even painful.
Re: Open Problems in Robotics
#84Earlier quoted context omitted.
Humans are capable of generating and understanding creativity and complexity that are simply impossible for non-AGI automation. Even then, we don't just let people figure things out for themselves. We put them through training, and then test them. Even after that, we make them liable for negligence. I don't think it's an obvious conclusion that error bounds aren't important for automation because they aren't calculab…
My point is not that it's not important. If someone comes up with a rigorous way to obtain error bars, that's great! I'll take it! My point is that trust should not and will not depend on it. How do you even quantify something like this to a layperson in order to persuade them? Let's do a thought experiment: let's say, we had a self-driving car that's verifiably 10x better than human on average, yet does not provide…
A human whose life is at stake controlling a car here at this moment vs a human who is far in space and time controlling someone else's car by programming it.
Re: Open Problems in Robotics
#85One problem I encountered while working on robotics is that many commonly used algorithms yield approximate solutions with no error bounds. They work 99.99‰ of the time. This is fine from a computer science or math point of view, but very scary from an engineering perspective, specifically when there are humans nearby. A big part of me struggles to accept the suitability of algorithms coming from gaming engines or ma…
Many localisation algorithms are probabilistic, eg. 'you are here within R of X'. A couple of times I've had a manager who could just not accept the probabilistic nature: "It's just right there!" So I to explain my manager that we just cannot do better and know for sure that the robot is really in position X, especially with the limited sensing the project would afford. Sure, you can do the classic AGV thing and add…
Why bother, you'll hit the uncertainty principle sooner or later anyway.
Re: Open Problems in Robotics
#86One problem I encountered while working on robotics is that many commonly used algorithms yield approximate solutions with no error bounds. They work 99.99‰ of the time. This is fine from a computer science or math point of view, but very scary from an engineering perspective, specifically when there are humans nearby. A big part of me struggles to accept the suitability of algorithms coming from gaming engines or ma…
Though, probably humans fumble or bump things >1/10k times. I certainly do, anyways.
Also, replace deer with something self driving. Those things are so stupid when near the road.
Re: Open Problems in Robotics
#87- Motion planning: already discussed. - Multiaxis singularities: much less of a problem than it used to be. We don't need closed-form solutions any more; we have enough CPU power at the robot to deal with this. You need some additional constraint, like "minimize jerk" when you have too many degrees of freedom. - Simultaneous Location and Mapping. SLAM for short: Getting much better. Things which explore and return a…
"The real problem: solve any of these problems, make very little money" - Just curious why have you come to this conclusion ? Object manipulation has potential products in dishwashing and vegetable chopping - sufficiently large markets, potential billion $ outcomes for a startup which takes the early mover lead. Two robotic hands that can work in co-ordination just as human hands do. Extremely difficult to solve, but…
I'm not the OP, but the real issue in robotics is two-fold and he mention both.
1. The cost & technical limitation. The cost, as some of the solution per problem OP suggest include "Lidar, visions and sensor" and all of those thing cost a lot by themselves. On top of that you need good actuators (Harmonic drives etc) for precision, and then good computing unit to handle all of it. Now you also need more power supply, and if it is mobile it needs a battery. Now your robot have a price tag only Arabic princes and well funded academic labs are interested in. And we haven't even touched the cost of try&fail iterative engineering process to make these work. In that process most companies/labs realizes the problem/condition have to be severely limited (run time, indoor/outdoor, general applicability vs made for one & one application only).
2. Human resource. Really, there's not much money in robotics, as a robotics engineer. Software robotics engineer can get a better working condition, security, salary & fulfillment in a software company. Mechanical, EE, embedded, etc is in a similar situation. Most robotics people I know are in for the passion. Application specific development (that is the norm right now) also require very niche knowledge that is hard to find.
Re: Open Problems in Robotics
#88Robotics founder here. Popular conceptions of "robots" are unrealistically general. In industry, we do not build robots, we build automation systems. Given the choice, would you prefer an automation system with some environmental assumptions, high speed and perfect repeatability (ie. entire industrial automation world), or no environmental assumptions, crushingly high cost, slow speed and poor reliability (eg. walkin…
Industrial automation is boring. Sure micron level accuracy sounds cool but it's so expensive it is only accessible for industrial automation. Only a tiny percentage of the population will ever be around those "robots".
I don't understand what you mean by crushingly high cost. You've saved most of the cost by reducing tolerance requirements such as zero backlash which will cost thousands of dollars for just a single gearbox.
Re: Open Problems in Robotics
#89Earlier quoted context omitted.
Build it. There is a global market of parents who will buy it. But on the other hand, why not accept the toys on the floor? You are fighting entropy for no reason. You sleep at night, you will work tomorrow during the day, and when you look again, the toys are in an equally dispersed state. Why not let them stay in that state for days until you need to hover?
Isn't life just one big fight against entropy?
Technically it isn't. Life needs entropy for variations and evolution. Also, life doesn't fight. It's identities that fight to maintain themselves. Life just keeps on living.
Re: Open Problems in Robotics
#90Earlier quoted context omitted.
This is the scariest part of using machine learning as an engineer on any practical application as well. Without an error bound, ML can’t be in charge of anything that could put human lives at risk. This is also why I don’t understand all the hype about FSD / L5 autonomous driving. We don’t even know yet if such error bounds even exist, so we don’t even know if machine learning is even the right tool for FSD yet. All…
> Without an error bound, ML can’t be in charge of anything that could put human lives at risk Humans don't have "error bounds" either, and you trust them just fine.
Two counterpoints here:
1) Humans can estimate their own uncertainty. Ask a person to show how long a meter is, and they'll give you an estimate. Then ask them to show you the "error bounds", i.e. what they're "quite certain" the meter is longer than and shorter than. You are likely to get sensible bounds. Now, humans aren't amazing at this, but the brain does have capacity for estimating how uncertain it is.
2) No, you don't really trust humans. This very fact that humans are often imperfect in estimating their own uncertainty makes us very stupid sometimes. How many times you were sure you know something for a fact, for it to turn out to be completely false. This is why society tries to not put too much responsibility into the hands of a single person, or at least to provide help and/or safety mechanisms if that is the case.