Files
miSim/@miSim/constrainMotion.m

61 lines
2.1 KiB
Matlab

function [obj] = constrainMotion(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
if size(obj.agents, 1) < 2
return;
% this doesn't work right now with only one agent
end
agents = [obj.agents{:}];
v = reshape(([agents.pos] - [agents.lastPos])./obj.timestep, 3, size(obj.agents, 1))';
h = NaN(size(obj.agents, 1));
h(logical(eye(size(obj.agents, 1)))) = 0; % self value is 0
nCon = nchoosek(size(obj.agents, 1), 2);
kk = 1;
A = zeros(nCon, 3 * size(obj.agents, 1));
b = zeros(nCon, 1);
for ii = 1:(size(obj.agents, 1) - 1)
for jj = (ii + 1):size(obj.agents, 1)
h(ii, jj) = norm(agents(ii).pos - agents(jj).pos)^2 - (agents(ii).collisionGeometry.radius + agents(jj).collisionGeometry.radius)^2;
h(jj, ii) = h(ii, jj);
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (agents(ii).pos - agents(jj).pos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
b(kk) = obj.barrierGain * h(ii, jj)^3;
kk = kk + 1;
end
end
% Solve QP program generated earlier
vhat = reshape(v', 3 * size(obj.agents, 1), 1);
H = 2 * eye(3 * size(obj.agents, 1));
f = -2 * vhat;
% Update solution based on constraints
opt = optimoptions('quadprog', 'Display', 'off');
[vNew, ~, exitflag] = quadprog(sparse(H), double(f), A, b, [],[], [], [], [], opt);
vNew = reshape(vNew, 3, size(obj.agents, 1))';
if exitflag <= 0
warning("QP failed, continuing with unconstrained solution...")
vNew = v;
end
% Update the "next position" that was previously set by unconstrained
% GA using the constrained solution produced here
for ii = 1:size(vNew, 1)
obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
end
% Here we run this at the simulation level, but in reality there is no
% parent level, so this would be run independently on each agent.
% Running at the simulation level is just meant to simplify the
% simulation
end