From 6bde513d2f919ab8d1f712aaa7933eda7a750d09 Mon Sep 17 00:00:00 2001
From: Sylvain CALINON <sylvain.calinon@idiap.ch>
Date: Sat, 3 Sep 2022 11:28:27 +0200
Subject: [PATCH] Updated description
---
README.md | 2 +-
python/IK.py | 16 ++++++++--------
2 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/README.md b/README.md
index e2feff0..628fa30 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Robotics codes from scratch (RCFS)
-RCFS is a collection of source codes to study robotics through simple 2D examples. Most examples are coded in Python and Matlab/Octave (full compatibility with GNU Octave). Some are also coded in C++ and Julia. The code examples have .m, .py, .cpp and .jl extensions that can be found in their respective folders matlab, python, cpp and julia.
+Robotics codes from scratch (RCFS) is a collection of source codes to study and test learning and optimization problems in robotics through simple 2D examples. Most examples are coded in Python and Matlab/Octave (full compatibility with GNU Octave). Some are also coded in C++ and Julia. The code examples have .m, .py, .cpp and .jl extensions that can be found in their respective folders matlab, python, cpp and julia.
### List of examples
diff --git a/python/IK.py b/python/IK.py
index 88224b6..f7055bf 100644
--- a/python/IK.py
+++ b/python/IK.py
@@ -20,7 +20,7 @@
'''
import numpy as np
-import matplotlib.pyplot as fig
+import matplotlib.pyplot as plt
# Forward kinematics for all joints (in robot coordinate system)
def fkin0(x, param):
@@ -49,8 +49,8 @@ param = lambda: None # Lazy way to define an empty class in python
param.dt = 1e-2 # Time step length
param.nbData = 50 # Number of datapoints
param.nbVarX = 3 # State space dimension (x1,x2,x3)
-param.nbVarF = 2 # Objective function dimension (position of the end-effector
-param.l = [2,2,1] # Robot links lengths
+param.nbVarF = 3 # Objective function dimension (position and orientation of the end-effector)
+param.l = [2, 2, 1] # Robot links lengths
fh = np.array([-2, 1]) #Desired target for the end-effector
x = np.ones(param.nbVarX) * np.pi / param.nbVarX #Initial robot pose
@@ -59,13 +59,13 @@ x = np.ones(param.nbVarX) * np.pi / param.nbVarX #Initial robot pose
## Inverse kinematics (IK)
# ===============================
-fig.scatter(fh[0], fh[1], color='r', marker='.', s=10**2) #Plot target
+plt.scatter(fh[0], fh[1], color='r', marker='.', s=10**2) #Plot target
for t in range(param.nbData):
f = fkin0(x, param) #Forward kinematics (for all articulations, including end-effector)
J = Jkin(x, param) #Jacobian (for end-effector)
x += np.linalg.pinv(J) @ (fh - f[:,-1]) * 10 * param.dt #Update state
- fig.plot(f[0,:], f[1,:], color='k', linewidth=1) #Plot robot
+ plt.plot(f[0,:], f[1,:], color='k', linewidth=1) #Plot robot
-fig.axis('off')
-fig.axis('equal')
-fig.show()
+plt.axis('off')
+plt.axis('equal')
+plt.show()
--
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