Hi,
Since there is so much vibration in my application, I want to use your low_pass_filter to reduce it,but I encounter some problems.
According to your example in kuka_driver.cc, I applied it into my project. This is the pseudo-code:
cutoff_hz = 250;
q_diff = currentJointPosition - previousJointPosition;
robot_dt = utime_now - utime_last_; // 0.004s
joint_velocity_estimated = vel_filters_[i].filter(q_diff/robot_dt)
// kTimeStep =0.004s
diffToGoal = joint_velocity_estimated*kTimeStep;
utime_last_ = utime_now;
commandToSend = currentJointPosition + diffToGoal;
commandToSendPlusIPOJointPos = commandToSend + ipoJointPosition;
// Then send commandToSendPlusIPOJointPos to robot in every kTimeStep.
Is this procedure OK?
It seems strange to me that robot couldn't follow the path I planed.
I'm wondering if it is caused by diffToGoal = joint_velocity_estimated*kTimeStep, since I didn't find anything about how to integrate joint_velocity_estimated to commandPosition.
Would you please give me some suggestions or instructions?
Thanks,
Chunting
Hi,
Since there is so much vibration in my application, I want to use your low_pass_filter to reduce it,but I encounter some problems.
According to your example in kuka_driver.cc, I applied it into my project. This is the pseudo-code:
Is this procedure OK?
It seems strange to me that robot couldn't follow the path I planed.
I'm wondering if it is caused by diffToGoal = joint_velocity_estimated*kTimeStep, since I didn't find anything about how to integrate joint_velocity_estimated to commandPosition.
Would you please give me some suggestions or instructions?
Thanks,
Chunting