Using MatLab show the implementation of Bug-1: Robot goes towards the goal until

Question

Using MatLab show the implementation of Bug-1: Robot goes towards the goal until it hits an obstacle. When an obstacle is encountered, the robot encircles the obstacle and then goes to the point on the boundary of the obstacle which is nearest to the goal. The algorithm is terminated when the goal is reached.

obstacle1.txt:

1
4
-8.052000 -6.720000
4.576000 7.933333
1.408000 8.353333
-11.000000 -5.040000
3 1 2
3 0 1

obstacle2.txt:

3

12
-8.140000 7.980000
-11.000000 6.953333
-12.320000 5.273333
-12.188000 3.406667
-11.088000 1.773333
-9.020000 1.120000
-7.304000 1.400000
-5.588000 2.286667
-4.224000 3.546667
-3.520000 5.413333
-4.312000 7.933333
-6.380000 8.586666

18
-9.108000 -9.613333
-8.888000 -10.593333
-7.612000 -10.686666
-5.500000 -9.566666
-3.124000 -7.420000
-0.088000 -4.106666
1.804000 -0.606667
3.256000 3.500000
4.268000 7.233333
5.148000 8.026666
5.148000 8.820000
4.488000 9.006666
2.728000 8.120000
1.188000 4.666666
0.484000 0.606667
-1.408000 -2.753333
-4.312000 -5.880000
-7.612000 -8.960000

6
7.832000 -0.980000
5.236000 -8.540000
9.988000 -10.500000
11.572000 -9.426666
7.524000 -7.793333
9.636000 -1.306667

"Bug 1" algorithm 1) head toward goal 2) if an obstacle is encountered, circumnavigate it and remember how close you get to the goal 3)return to that closest point (by wall-following) and continue

Explanation / Answer

options = struct;
    options.name = 'Obstacle avoidance';
    constr = {cbox, cbnd, ode, obstacles};
    solution = ezsolve(objective, constr, x0, options);

    % Optimum x, y, and speed, to use as starting guess in the next iteration
    xopt = subs(x, solution);
    yopt = subs(y, solution);
    vxopt = subs(vx, solution);
    vyopt = subs(vy, solution);
    thetaopt = subs(theta, solution);
    speed = subs(V,solution);

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