Good question! The great news is that the maker movement has meant lots of the parts you'd use in robotics are now accessible and cheap! For example, you can buy Dynamixel AX-12 robot servos and build your own robot arm for ~$400-$1000. This gives you servos that have accurate positioning and feedback, unlike the super-budget arms that you can get for $100ish.
You can buy robot platforms and sensors from companies like DFRobot, Adafruit, Sparkfun, etc. Hobby 2-D lidar? $300-400. Plenty for personal projects & learning.
> should I buy industrial robot arms and build personal project of automating simple tasks with computer vision, machine control, and machine learning?
It sounds to me that you're interested in the software side of the space. My personal recommendation is if say you're interested in reinforcement learning to learn the algorithms in simulation like Mujoco and Unity. Sure, algorithms that work in sim don't move nicely to the real world, but you don't need your thing to work in real world to learn how it works. And if you _wanted_ to try it in the real world, you could go and learn the hardwarey things. Similarly, if you're interested in supervised learning or vision, you don't need to build robots.
Planning and control you can probably do a lot in sim too but those things have a lot of theory behind them that might be nice to learn in the classroom setting. If I were trying to be a planning & control engineer I'd probably look into a coursera course or something. Thing to remember about RL for control & planning right now is that it doesn't quite work yet.
You can buy robot platforms and sensors from companies like DFRobot, Adafruit, Sparkfun, etc. Hobby 2-D lidar? $300-400. Plenty for personal projects & learning.
> should I buy industrial robot arms and build personal project of automating simple tasks with computer vision, machine control, and machine learning?
It sounds to me that you're interested in the software side of the space. My personal recommendation is if say you're interested in reinforcement learning to learn the algorithms in simulation like Mujoco and Unity. Sure, algorithms that work in sim don't move nicely to the real world, but you don't need your thing to work in real world to learn how it works. And if you _wanted_ to try it in the real world, you could go and learn the hardwarey things. Similarly, if you're interested in supervised learning or vision, you don't need to build robots.
Planning and control you can probably do a lot in sim too but those things have a lot of theory behind them that might be nice to learn in the classroom setting. If I were trying to be a planning & control engineer I'd probably look into a coursera course or something. Thing to remember about RL for control & planning right now is that it doesn't quite work yet.