- This is a research project led by Alexander Elias and Dr. John Wen at RPI.
- Summation of research: https://arxiv.org/pdf/2211.05737.pdf
- Included here is the Python version of the MATLAB-based canonical subproblems for inverse kinematics on robots.
- Additional MATLAB, C++, Rust, and Python files are located at https://github.com/rpiRobotics/linear-subproblem-solutions/.
- NumPy: https://numpy.org/install/
- SciPy: https://scipy.org/install/
- Python (version compatible w/ installed NumPy)
- Clone the above repo
- To see timing information and a simple demo, run each sp#.py file
- Otherwise, just include yhe pip module in your applications as needed
- NumPy vs MATLAB can be confusing at first, see this article for some clarity.
- See the below note on precision/formatting.
- NumPy makes it extremely easy to export/import entire matrices as csv/excel files. Make use of this if you can.
- If comparing values in Python to MATLAB output, be careful with how inputs are entered.
- Also, note that values printed in the test files are not the exact values used in the calculations.
- Vectors in NumPy are of form [n n n] (0 row, 3 col). You cannot have a vector of 3 col, 0 row.
- Note, the MATLAB version of this code uses vectors of 3 col, 0 row, which is why some calculations look slightly different.
p1 = [0.85421456 0.9145417 0.28164908]
p2 = [0.71384302 0.84785577 0.40390217]
k1 = [0.53432959 0.73260445 0.42164275]
k2 = [0.89871158 0.33336884 0.2849258 ]
p1 = [0.85421456; 0.9145417; 0.28164908]
p2 = [0.71384302; 0.84785577; 0.40390217]
k1 = [0.53432959; 0.73260445; 0.42164275]
k2 = [0.89871158; 0.33336884; 0.2849258 ]
| Subproblem | Time With Inputs | Time Without Inputs |
|---|---|---|
| Sp1 | 78716.896 ns | 73754.058 ns |
| Sp2 | 325238.43 ns | 318135.293 ns |
| Sp2E | 409206.773 ns | 400298.479 ns |
| Sp3 | 127781.537 ns | 122444.399 ns |
| Sp4 | 104747.862 ns | 99615.851 ns |
| Sp5 | 1353110.805 ns | 1341531.159 ns |
| Sp6 | 614233.523 ns | 596708.225 ns |