Paper Simulation Save

Let's reproduce paper simulations of multi-robot systems, formation control, distributed optimization and cooperative manipulation.

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Let's Reproduce Paper Simulations!

Some paper simulations by matlab for multi-robot systems, formation control, distributed optimization and cooperative manipulation. If you have any interesting papers that are hard to reproduce the simulations, feel free to share with me!

Here are the list of paper simulations I have reproduced.

  1. Alonso-Mora, J., Baker, S., & Rus, D. (2017). Multi-robot formation control and object transport in dynamic environments via constrained optimization. International Journal of Robotics Research, 36(9), 1000–1021. https://doi.org/10.1177/0278364917719333
  2. Farivarnejad, H., & Berman, S. (2018). Stability and Convergence Analysis of a Decentralized Proportional-Integral Control Strategy for Collective Transport. Proceedings of the American Control Conference, 2018-June, 2794–2801. https://doi.org/10.23919/ACC.2018.8431618
  3. Zhao, S. (2018). Affine Formation Maneuver Control of Multiagent Systems. IEEE Transactions on Automatic Control, 63(12), 4140–4155. https://doi.org/10.1109/TAC.2018.2798805
  4. Ibuki, T., Wilson, S., Yamauchi, J., Fujita, M., & Egerstedt, M. (2020). Optimization-based distributed flocking control for multiple rigid bodies. IEEE Robotics and Automation Letters, 5(2), 1891–1898. https://doi.org/10.1109/LRA.2020.2969950
  5. Kia, S. S., Cortés, J., & Martínez, S. (2015). Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication. In Automatica (Vol. 55, pp. 254–264). Elsevier Ltd. https://doi.org/10.1016/j.automatica.2015.03.001
  6. Sun, S., & Ren, W. (2020). Distributed Continuous-Time Optimization with Time-Varying Objective Functions and Inequality Constraints. Retrieved from http://arxiv.org/abs/2009.02378
  7. Antonelli, G., Arrichiello, F., Caccavale, F., & Marino, A. (2013). A decentralized controller-observer scheme for multi-agent weighted centroid tracking. IEEE Transactions on Automatic Control, 58(5), 1310–1316. https://doi.org/10.1109/TAC.2012.2220032
  8. Shi, W., Ling, Q., Wu, G., & Yin, W. (2015). Extra: An exact first-order a lgorithm for decentralized consensus optimization. SIAM Journal on Optimization, 25(2), 944–966. https://doi.org/10.1137/14096668X
  9. Jakovetić, D. (2019). A Unification and Generalization of Exact Distributed First-Order Methods. IEEE Transactions on Signal and Information Processing over Networks, 5(1), 31–46. https://doi.org/10.1109/TSIPN.2018.2846183
  10. Qu, G., & Li, N. (2018). Harnessing smoothness to accelerate distributed optimization. IEEE Transactions on Control of Network Systems, 5(3), 1245–1260. https://doi.org/10.1109/TCNS.2017.2698261
  11. Zhang, M., Liu, X., & Liu, J. (2021). Convergence Analysis of a Continuous-Time Distributed Gradient Descent Algorithm. IEEE Control Systems Letters, 5(4), 1339–1344. https://doi.org/10.1109/LCSYS.2020.3037038

Requirements

  1. MOSEK-MATLAB or CVX
  2. Robotics-Toolbox.

More Tutorials

See my CSDN blog or my Github Pages.

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