Some records of arXiv papers, GRASP seminars, and resources during my PhD period.
- ICRA 2023 MW07: Energy Efficient Aerial Robotic Systems
- ICRA 2023 FW30: Active methods in autonomous navigation
- IROS 2023 Workshop on Integrated Perception, Planning, and Control for Physically and Contextually-Aware Robot Autonomy
- CDC 2023 Workshop on Benchmarking, Reproducibility, and Open-Source Code in Controls
- IROS 2023 Workshop on Leveraging Models for Contact-Rich Manipulation
The papers and notes are updated weekly, mainly about motion planning.
These are the robotic labs I pay special attention to.
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MADER: Trajectory Planner in Multi-Agent and Dynamic Environments
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Downwash-Aware Trajectory Planning for Large Quadcopter Teams
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Policy Search for Model Predictive Control with Application to Agile Drone Flight
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Model Predictive Control for Multi-MAV Collision Avoidance in Dynamic Environments
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- Use: automatic control and dynamic optimization. It can solve MPC, but has some limits
- License: open source
- Interface: C++, with MATLAB
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- Use: nonlinear optimization and algorithmic differentiation
- License: open source
- Interface: C++, Python or Matlab/Octave
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- Use: code generator for optimization solver, very useful to solve nonlinear MPC
- License: Academic Licenses
- Interface: C++, Python or Matlab /Simulink interface
- Some examples: https://github.com/embotech/forcesnlp-examples
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- Use: non-linear Least Squares with bounds constraints/ unconstrained optimization
- License: open source
- Interface: C++ library
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- Use: linear/quadratic/semidefinite solver
- License: open source
- Interface: Matlab/Octave
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- Use: non-linear numerical optimization
- License: open source
- Interface: C++ library
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- Use: large scale sparse linear programming
- License: open source
- Interface: C, C#, FORTRAN, Julia and Python
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- Use: Google Optimization Tools
- License: open source
- Interface: C++, but also provide wrappers in Python, C# and Java
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- Use: IBM optimization studio
- License: have Free Edition
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- Use: robotic toolbox, can solve optimizations, systems modeling, and etc.
- License: open source
- Interface: C++, python
- Some examples: https://github.com/RobotLocomotion/drake-external-examples
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- Use: some types of optimizations. conic, QP, SDP...
- License: Academic Licenses
- Interface: C++, C, python, Matlab
- Tutorials: https://github.com/MOSEK/Tutorials
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- Use: QP
- License: MA27 from the HSL Archive
- Interface: object-oriented C++ package
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- Use: LP, QP and MIP (MILP, MIQP, and MIQCP)
- License: Academic Licenses
- Interface: C++, C, Python, matlab, R...
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- Use: for convex second-order cone programs (SOCPs)
- License: open source
- Interface: C, Python, Julia, R, Matlab