Sampling-based Motion Planning via Control Barrier Functions
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Calin Belta | Roberto Tron | Guang Yang | Zachary T. Serlin | Bee Vang | Zachary Serlin | C. Belta | Guang Yang | Roberto Tron | Bee Vang
[1] B. Faverjon,et al. Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .
[2] Emilio Frazzoli,et al. Sampling-based algorithms for optimal motion planning , 2011, Int. J. Robotics Res..
[3] Robert Platt,et al. Optimal sampling-based planning for linear-quadratic kinodynamic systems , 2013, 2013 IEEE International Conference on Robotics and Automation.
[4] Hung Manh La,et al. Dynamic path planning and replanning for mobile robots using RRT , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[5] L. Leemis. Applied Linear Regression Models , 1991 .
[6] Mo Chen,et al. FaSTrack: A modular framework for fast and guaranteed safe motion planning , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).
[7] Nahum Shimkin,et al. Nonlinear Control Systems , 2008 .
[8] Aaron D. Ames,et al. Control barrier function based quadratic programs with application to bipedal robotic walking , 2015, 2015 American Control Conference (ACC).
[9] Calin Belta,et al. Control Barrier Functions for Systems with High Relative Degree , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).
[10] Koushil Sreenath,et al. Exponential Control Barrier Functions for enforcing high relative-degree safety-critical constraints , 2016, 2016 American Control Conference (ACC).
[11] J. How,et al. Receding horizon path planning with implicit safety guarantees , 2004, Proceedings of the 2004 American Control Conference.
[12] J. Neter,et al. Applied Linear Regression Models , 1983 .
[13] Paulo Tabuada,et al. Control barrier function based quadratic programs with application to adaptive cruise control , 2014, 53rd IEEE Conference on Decision and Control.
[14] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[15] S. LaValle. Rapidly-exploring random trees : a new tool for path planning , 1998 .
[16] Li Wang,et al. Control Barrier Certificates for Safe Swarm Behavior , 2015, ADHS.
[17] Jur P. van den Berg,et al. Kinodynamic RRT*: Asymptotically optimal motion planning for robots with linear dynamics , 2013, 2013 IEEE International Conference on Robotics and Automation.
[18] Olzhas Adiyatov,et al. A novel RRT*-based algorithm for motion planning in Dynamic environments , 2017, 2017 IEEE International Conference on Mechatronics and Automation (ICMA).
[19] Leslie Pack Kaelbling,et al. LQR-RRT*: Optimal sampling-based motion planning with automatically derived extension heuristics , 2012, 2012 IEEE International Conference on Robotics and Automation.