AI optimal rotation of a rigid body

chiro

What I mean is to make the parameter you pass (i.e. t between 0 and 1 inclusive) to vary non-linearly. Instead of going from 0 to 1 in incremental steps that are the same, you can make it go say faster at the start and then let it decay at the end.

Different kinds of behaviours for f(t) where f(t) is in [0,1] and t is in [0,1] give different kinds of behaviours for how the AI rotates itself to approach the target.

If you are continually updating the path every tick so that the SLERP changes in accordance with the new position, then you can base the behaviour of f(t) on things like the dot product of the direction vector of the ship and the vector of the actual ship itself: speed it up when they are not aligned (i.e. dot product < 0) and then make it slow down when they are close (dot product > .05 for example)

You can, by transforming the parameter and how its incremented, directly control how the object moves and what it looks like when it rotates.

Snark1994

Thanks, I understand that a non-linear parameter will give the appearance of an accel/decel rotation, but that's more applicable to animation. I also can't see how it would cope with the case where e.g. the ship is at (Y,P,R) = (90,0,0), wants to get to (0,90,0) and is initially rotating around the yaw axis at 10 deg/second - as the path the ship would take is no longer a linear interpolation but a curve.

I think I can get it to work using something similar to http://www.shiffman.net/itp/classes/...09/seekarrive/ but for rotations. I'm going off on holidays now, and it's not quite working but I suspect it's due to a bug rather than a problem with the method, so I'll see if I can get it fixed when I get back - if I do, I'll post back here with my algorithm.

Thanks for all the suggestions so far!

Snark1994

Well, I haven't got C++ working but my python seems to be working well enough - using the seek/arrive steering behaviour I posted in my last post:

Code:

#!/usr/bin/env python3

from math import sqrt,sin,cos,acos

rot_thrust = 0.01 #degrees per timestep
DEGTORAD = 0.0174532

def main():
        rot = Quaternion(1/sqrt(2),0,0,-1/sqrt(2))
        drot = Quaternion(cos(30*rot_thrust*DEGTORAD),0,sin(30*rot_thrust*DEGTORAD),0)
	d2rot = Quaternion(1,0,0,0)

	goal = Vector(0,5,0)
	step = 0

	while abs(rot.w - 1) > 0.00000001:
		step += 1
		d2rot = steer(rot,drot,goal)
		drot = d2rot * drot
		rot = drot * rot

def steer(rot,drot,goal):
	desired_drot = get_desired_drot(goal,rot,drot)
	desired_d2rot = (desired_drot * drot.inverse()).normalise()
	return get_d2rot(desired_d2rot)

def get_desired_drot(goal,rot,drot):
	slow_down_dist = 90*DEGTORAD #radians
	max_speed = 0.0146221 #radians per timestep

	dot = Vector(0,1,0).dot(goal.normalise());
	axis = goal.cross(Vector(0,1,0)).normalise()
	alpha = acos(dot)
	if axis == None and dot == 1: #parallel
		desired_rot = Quaternion(1,0,0,0)
	elif axis == None and dot == -1: #opposite
		desired_rot = Quaternion(0,1,0,0)
	else:
                desired_rot = Quaternion(cos(alpha/2),axis.x*sin(alpha/2),axis.y*sin(alpha/2),axis.z*sin(alpha/2))

        to_desired = (desired_rot * rot.inverse()).normalise()
        dist = acos(to_desired.w)*2;
        if dist > 0:
                axis = Vector(to_desired.x,to_desired.y,to_desired.z).normalise()
                if dist < slow_down_dist:
                        theta = max_speed*dist/slow_down_dist
                else:
                        theta = max_speed
                return Quaternion(cos(theta/2),axis.x*sin(theta/2),axis.y*sin(theta/2),axis.z*sin(theta/2))
        else:
                return Quaternion(1,0,0,0)

def get_d2rot(desired):
        axis = Vector(desired.x,desired.y,desired.z).normalise()
        desired_theta = acos(desired.w)*2
        assert(desired_theta >= 0)
        theta = min(desired_theta,rot_thrust*DEGTORAD)
        return Quaternion(cos(theta/2),axis.x*sin(theta/2),axis.y*sin(theta/2),axis.z*sin(theta/2))

With a sensible definition of the Quaternion and Vector classes. Hope this helps someone!

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