Multi Dimensional Tracking Algorithm
This algorithm is used for multi-dimensional robot based MF tracking.
In this document position-tracking is presented.
Position is considered to be a 3-dimensional vector with its derivatives (velocity, acceleration, jerk): , ,
The algorithm consist of a state machine with the following states:
- Tracking process
- Full Synchronization follow the master
- Stopping (de-synchronization process)
State: Full Synchronization follow the master
- Check if master velocity or acceleration exceeds max master frame's values if yes return an error
- copying all derivatives
- reset: flopstime = flops = 0
State: Tracking process
Initial Setup and testing
Value of AccMaxTran is used of checking of acceleration limit.
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Value of VelMaxTran is used of checking of velocity limit.
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- Check if master velocity or acceleration exceeds max master frame's values if yes return an error
pure delta-position
pure delta-velocity
Time-to-Reach initial estimation
This is an estimation of time needed to reach the target. It is not an exact formula
if the slave velocity is lower then master's we need more time: once to get to a higher velocity then the masters and once
to get from that (higher) velocity to the masters - therefore the multiplication by 2
where
Additionaly we mutliply by a prediction factor - to decrease acc/jerk
(rounding to integer number of samples):
time_to_reach *= DampingFactor
time_to_reach = T*int(time_to_reach/T+1)
Prediction of the Rendezvous-Point
The predicted position of the rendezvous (minus T, if it will happen in this sample!)
: position prediction assuming constant acceleration
: Predicted position difference
: velocity prediction
Assuming the acceleration will be zero:
Polynomial coefficients of 5-degree polynom connecting the current p,v,a to the randevous p,v,a
- not used, directly written into code
- not used, directly written into code
- not used, directly written into code
Next Sample Position
The position at the next sample will be:
Initial increment (full displacement):
The acceleration and jerk increments could be computed in this way also.
But they are computed as average values for the time of sample duration, this approach does fit more to
the tools we are using to test this feature, as they all compute acceleration & jerk by numeric differentiation
inside one sample.
The side effect of all this is that we can have a change in jerk/acc sign inside one sample and the average value we are using
ddp,dddp could have an opposite sign, so we are seeing effects like jerk or acceleration is limited from a "wrong side" i.e. instead
using jmax -jmax is used. There is not much we can do against it, using exact jerk/acc values (from polynom) returns than wrong average values
we observe as jerk/acc exceed over their max values. So the average value approach is not perfect but gives results within the given limits.
Initial setting of predicted time and the filter limit flag (if the filter did work - this flag will be on)
limit = false
state.satVel = false
state.satAcc = false
state.satJrk = false
Velocity, Acceleration and Jerk Filter
where i.e. unit vector
Setting Initial velocity delta
Setting Initial acceleration delta
New position is:
If the filter was activated then:
if the velocity,accleration or jerk is limited (limit = true) then the velocity computed using polynomials does
Velocity & Accleration will be computed exactly not using dp and ddp, it has been shown that this
approach is much better - means more stable
keep the old values for next sample
System is synchronized if NEW delta's are under certesian thresholds:
; - keep the previous dv
Successful tracking completion
if and
Synchronization
Take the middle for an additional smoothing:
ResetFilter(); // Reset the filter
state.tracking = MOT_MASTER_SYNC; // System synchronized<br>
else if( dv0*dv < 0)
Check against over-oscillation
if (flops == -1) flops = 0; // ignore the first sample
else flops++;
flopstime = 0;
Over-Oscillation Check
if (flops > maxFlops && (flopstime > maxFlopsTime && fabs(dv) > syncGain * sync_accT2))
state.tracking = MOT_MASTER_OSC; // OScilationss
else
flopstime++;
State: Stopping (de-synchronization process)
flopstime = flops = 0;
- De-Syncing profile, follow the given profile, ignore the real source
- determine the curvature parameters path:
, ,
or linear movement:
- initialize stopping profile with current values of curvature angle:
desync.pos =
desync.vel =
desync.acc =
See: Theoretical_Background
- initialize the profiler for stopping - computing the stopping (deceleration path) ad set as new target position for the profiler.
desync.Profile();
or in case of linear motion:
if(desync.path.Status.stop) // if stopped,change the state to OFF
SetState(MOT_MASTER_OFF);