Modern Robotics: Mechanics, Planning, and Control – Free Textbook (2017)
hades.mech.northwestern.edu
hades.mech.northwestern.edu
I will highly recommend reading this textbook along with RM Murray's "A Mathematical Introduction to Robotic Manipulation" [1]. Both of these textbooks provide very intuitive and clear cut explaination of principles behing robotic motion and planning.
I would also highly recommend completing a 5-course specialization on Coursera [2] by the same name as the first textbook. The course is conducted by the author, he uses plenty of great visualization to explain the concepts clearly and the course follows the textbook.
1. https://www.cds.caltech.edu/~murray/books/MLS/pdf/mls94-comp...
Replacing forward and inverse kinematics with machine learning is extremely simple, and avoids most of the problems these formulas have (for instance, they don't consider that a robot might attempt to move through itself). And while grasping and manipulation isn't simple even with machine learning, I think you'll agree that the theory in these books also very, very much isn't simple.
And the problem is that the current capabilities of robots using these formulas from books like these ... are insufficient. They need to become WAY more complex to be useful, but that's impossible: they're already damned complicated.
The outlook very much is that the only way we'll ever arrive at the required complexity for these machines is through machine learning, and if not that, then through some form of automated program writing. A human just cannot write safe and working code that deals with robots in open settings and/or where interactions might occur.
You should probably still learn the very basic parts. Chapter 9 and 11. But after that, you will likely get further with machine learning.
Could you point towards a good paper or review paper on using machine learning models to learn forward and inverse kinematics? How far can one get with plain old LSTMs?
Besides the courses recommended here this are other online materials related to planning, location and control I found really useful and consider to be high quality:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt... https://www.coursera.org/learn/mobile-robot
For Linear Algebra I really like Strang's course on OCW taken together with reading through his book.
Are examples of things that are hard for me to understand. Especially that 2d picture in 4.11
Learn to walk before you fly.
And none of those high flying concepts ever talk about those maintaining the robots. Those who never attended High School, who are okay with a 9000 line copy pasted Procedural program, and not okay with object orientation or even functional programing style.
Im so sick of all that wasted time in startups, where people like me fresh from university develop - new, idea robots, who will never take hold in a actual factory- because none of those revoluzzers wants to spend all its time in that factory, maintaining the robot- beeing the only one competent enough todo so.
Sorry if this is a rant, but i wish for once that economic reality would nuke some sense into the architects of that tomorrow that never comes. Maybee we could have small, nice things, if we where willing to do the little steps.