Randomized robot

A simple example program for force polytope evaluation of a randomised robot model. Simply change the number of dof torque limits and see how the calculation time and shape evaluates.

📢 NEW Examples!

For some more examples check out the examples folder of the repository.

• Interactive jupyter notebooks are available in the examples/notebooks folder: see on Github

import pycapacity.robot as capacity # robot capacity module
import numpy as np

m = 3 # 3d forces
n = 6 # robot dof 

# this seed is used to generate the same image 
# as in the examples in the docs 
np.random.seed(12345)

J = np.array(np.random.rand(m,n)) # random jacobian matrix

t_max = np.ones(n)  # joint torque limits max and min
t_min = -np.ones(n)

f_poly = capacity.force_polytope(J,t_min, t_max) # calculate the polytope

print(f_poly.vertices) # display the vertices

# plotting the polytope
import matplotlib.pyplot as plt
from pycapacity.visual import * # pycapacity visualisation tools
fig = plt.figure(4)

# draw faces and vertices
plot_polytope(plot=plt, 
              polytope=f_poly, 
              label='force', 
              edge_color='black', 
              alpha = 0.4)

plt.legend()
plt.show()