We have a reverse dumping claw-tray hybrid. The claw is geared 1:5 with torque motors. We can realistically grab up to 2 cubes or 6 stars during a match. However, especially when we take these larger loads of objects, the claw motors tend to stall for a few seconds before coming back to life. This is obviously not ideal as a few seconds can make quite the difference. I attempted to add elastics which helped the claw close yet they did nothing for the stalling issue - the claw would just stall and hold shut. I know that there’s no friction issue causing this. Is anyone else having an issue like this? Could it be a motor or motor controller issue (which I find doubtful as the stalling occurs on both sides), or could this ratio potentially not offer the torque we would need for these larger loads. My concern with switching to 1:7, however, is sacrificing opening and closing speed which is also crucial in matches.
I have had the same problem with my last claw as well.
If possible, is there a way to fix this without using rubber bands?
I find that rubber bands make it more complicated to make accurate autonomous routines.
This is why many teams have a fork under the claw. Constantly pinching the stars can brown out the motors pretty easily. If a fork won’t work for you, some rubber band tension that holds the claws closed might. Also, depending on how the stars are lined up, you may be able to gently close around them and stop applying motor power – basically use your claws as a fork if you are picking up only a few.
We aren’t. We designed our claw in a way such that it has a mechanical stop (it only opens to the exact point we need it to and therefore it rids itself of any errors in the positions of each arm every time it fully opens), so we currently require no encoders or pots. That being said, if there is no good mechanical option, we can go that route.
PID is a calculus based closed control loop. Here’s the Wikipedia article on PID:
It’s used a lot in odometry. In Vex we use it a lot whenever we need to hit a target value, i.e. autonomous, lift positions, and claw positions.
A quick Google search will show a lot of examples for vex, so I won’t go into detail here. Basically there are 3 terms: proportional, integral, and derivative (hence the name PID) that interact with an error you calculate to very accurately reach a target value.