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- Hacker News
- Congrats on launching. This should get more attentionby sidcool
- Congrats on the launch! At Transitive Robotics we make full-stack modules so robotics companies like you can build their operational systems faster and with greater quality. We have a number of modules you might be interested in, e.g., for remote video-streaming and tele-op/-assist: https://transitiverobotics.com/caps/. Let me know if you want to chat.by chfritz
- Is "Salem" a tongue-in-cheek nod to being a small, quirky competitor to Boston Dynamics (Salem, MA : Boston, MA :: Salem Robotics : Boston Dynamics)?
If so, as someone who lives close to Salem, I like it :)
Good luck to you guys.
by droidjj - All the best! Very clear framing and definitely needed service. I remember in 2011 not too far from Fukushima after the problems with nuclear reactors. The company here faced very difficult inspection problems, including through rubbles. There were robots able to deal with some problems, but not in Japan, and anyway they had to act fast and so sent people. It apparently was safe enough, but able robots would have been so much safer.
A technical question: To scan a surface precisely, I'd rather put switches on the end effector aside the sensor, such that the arm places itself roughly above the surface to scan, pushes until the switches trigger, and scan keeping the switches on. A simple touch sense, basically. All trad robotics that smoothly follows many flat and curved surfaces. Not at all against AI here, it seems the whole thread is a constructive approach mixing the best tools to concrete targets. Not viable approach in your scenarios?
Thoughts on your concluding questions:
> where the abstraction boundary in robotics should sit. What should come from the robot manufacturer, what belongs in an application layer, and what will inevitably remain specific to the facility?
I really like when there is a "double SDK", with a low level one to target actuators and sensors individually (motor 2 of leg 4), and a higher level one with pre-defined scenarios (move forward, whatever the bot is a bipede, a quadcopter or a slug). These two API types often allow for easier work at the application layer. The SDK is also the main specific software that remains with the maker (facility?)
> industries where you've seen physical inspection tasks that look trivial to a person but are surprisingly difficult to automate
Too often a problem I have seen is... elevators. More generally unstructured environment, and environments explicitly tailored for humans. Proposals range from wireless interfaces (and so HW infrastructure dependent and hard to scale), to adding a manipulator to, say, push buttons on an elevator (and this means extra software to manipulate, recognise buttons, etc).
by hic - Congrats on the launch. I've been in the robotics industry for a decade now, I've seen that boundary lie at many different places. I'm not sure there's a clear cut answer.
Self plug: I'm the founder of Clipper, a container registry that has 10x faster pulls and 7x faster builds over DockerHub, targeted at robotics. I got tired of robotics deploys taking all day and fixed it myself. If you're interested in that or just want to talk shop, let's chat.
by a_t48
Congrats on the launch. I love this part, because it is also the working theory behind my robot clearing robot project (http://www.frost-e.com). I'm new to robotics, but it seems to me there's a gap between classic robotics tools and approaches (ROS2-based navigation, local YOLO-based object detection etc) and the video-input-to-actuator-output VLA models that robot labs are showcasing. In fact, I kinda think the big labs are trying to boil the ocean - long horizons, 6DoF actuator control, cross embodiment, generalization, etc etc.> We use AI where semantic understanding and flexibility are useful, such as interpreting less structured information or understanding what in an unfamiliar scene is relevant to a procedure. Once the system knows what physical interaction it needs to perform, we prefer explicit geometry, planning, optimization, and control where possible. We're interested in the marriage between the two rather than trying to make every part of the robotics stack learned.Seems to me is that if you restrict the problem space, have well defined tasks, then marry the semantic understanding and reasoning of VLMs with the geometric tools of classical approaches, then you could have something practical and economical.
- The part about being hardware-agnostic sounds something like ROS 2, but maybe at a higher level. I would love to see a post about that (with a bit of explainers for people like me who only lightly dabble with robotics).
But I'm also curious to know if the "Salem" name was searched first. When I first saw the title I thought it was talking about Agility Robotics, which is based in Salem, Oregon and is currently 3rd spot on Google search for "Salem Robotics" (and 4 of the top 5 results on YouTube).
by beckford - > We use AI where semantic understanding and flexibility are useful, such as interpreting less structured information or understanding what in an unfamiliar scene is relevant to a procedure. Once the system knows what physical interaction it needs to perform, we prefer explicit geometry, planning, optimization, and control where possible...
> A few centimeters of error may not matter much when navigating down a hallway, but it matters if a sensor is supposed to remain normal to a curved surface.
This is a great specific example of where the creativity (read: randomness) of AI runs into a wall. Do you see this changing over time as models improve, or do you expect that safety-critical / highly specific tasks will always require a more explicit set of instructions?
by lesiva