Pinned Repositories
6DOF-Robot-Dynamics
In this repository, dynamic model for 6DOF robot is derived using Euler-Lagrange approach. Inertia matrix, Coriolis matrix, and gravity vector are calculated. The repository is also a solution for Assignment4 in Dynamics of Nonlinear Robotics Systems course for ROCV master's program at Innopolis University.
abc-ds
ABC-DS: obstacle Avoidance with Barrier-Certified polynomial Dynamical Systems
abcc-ds
ABCC-DS: obstacle Avoidance with Barrier-Certified Compositional polynomial Dynamical Systems
abelian-tommyod
Computations on locally compact Abelian groups.
aerdg
Algorithm Engineering for Repartitioning Dynamic Graphs
book-code
cpp-docs
C++ Documentation
enclosos
EncloSOS: A MATLAB Toolbox for Computing Semi-Algebraic Enclosures
mimouse
Micromouse - Engineering a Mobile Robot from Scratch
neuropose
Neuromorphic Path Integration with Multiple Simultaneous Pose Estimates
martinschonger's Repositories
martinschonger/abc-ds
ABC-DS: obstacle Avoidance with Barrier-Certified polynomial Dynamical Systems
martinschonger/enclosos
EncloSOS: A MATLAB Toolbox for Computing Semi-Algebraic Enclosures
martinschonger/6DOF-Robot-Dynamics
In this repository, dynamic model for 6DOF robot is derived using Euler-Lagrange approach. Inertia matrix, Coriolis matrix, and gravity vector are calculated. The repository is also a solution for Assignment4 in Dynamics of Nonlinear Robotics Systems course for ROCV master's program at Innopolis University.
martinschonger/abcc-ds
ABCC-DS: obstacle Avoidance with Barrier-Certified Compositional polynomial Dynamical Systems
martinschonger/abelian-tommyod
Computations on locally compact Abelian groups.
martinschonger/aerdg
Algorithm Engineering for Repartitioning Dynamic Graphs
martinschonger/book-code
martinschonger/cpp-docs
C++ Documentation
martinschonger/mimouse
Micromouse - Engineering a Mobile Robot from Scratch
martinschonger/neuropose
Neuromorphic Path Integration with Multiple Simultaneous Pose Estimates
martinschonger/ds-opt
Toolbox including several techniques for estimation of Globally Asymptotically Stable Dynamical Systems from demonstrations. It focuses on the Linear Parameter Varying formulation with "physically-consistent" GMM mixing function and different constraint variants, as proposed in [1].
martinschonger/gridcells-diogosantospata
Implementation of grid cells in Python and Javascript
martinschonger/gridcells-lsolanka
Grid cell data analysis package.
martinschonger/hello-github-actions
martinschonger/icra19-lfd-tutorial-exercises
Set of exercises accompanying the ICRA 2019 Tutorial on Dynamical System based Learning from Demonstration: https://epfl-lasa.github.io/TutorialICRA2019.io/
martinschonger/lightspeed
lightspeed matlab toolbox
martinschonger/martinschonger
Config files for my GitHub profile.
martinschonger/martinschonger.github.io
martinschonger/martinschonger.github.io_archive2
martinschonger/mastersthesis
martinschonger/notion-zotero-redirect
martinschonger/phys-gmm
Physically-consistent GMM fitting approach proposed by Figueroa, N. and Billard, A. (2018) "A Physically-Consistent Bayesian Non-Parametric Mixture Model for Dynamical System Learning". In Proceedings of the 2nd Conference on Robot Learning (CoRL).
martinschonger/reciprocal-lattice-fkiaru
reciprocal lattice visualization tool
martinschonger/RSS2018Tutorial
A set of exercises related to the tutorial given in RSS2018
martinschonger/schonger.at_redirect