Real-time kinodynamic planning and dynamic optimization

Yajia Zhang, Jingru Luo, Kris Hauser


Planning costs cannot be ignored in dynamic, real-time systems. Powerful planners are unresponsive to unexpected changes, but weak planners sacrifice completeness and optimality. Moreover, improper integration can jeopardize robot performance and safety. To address these issues, this research theme investigates faster planners and better system integration architectures. New fast optimization techniques let robots execute motions more quickly while strictly respecting dynamic constraints; moreover, the added computational costs are worth the savings in execution time. New time-stepping architectures are proven to be asymptotically complete in a deterministic environment with changing goals, and experiments suggest improved safety in unpredictably dynamic environments compared to other state-of-the-art techniques. These algorithms have been applied to assisted teleoperation of a 6DOF robot arm, navigation amongst unpredictable moving obstacles, and humanoid robot locomotion.

  • K. Hauser and Y. Zhou. Asymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space. IEEE Transactions of Robotics, 32(6): 1431-1443, 2016. pdf link Also in arXiv:1505.04098 [cs.RO], 2015. pdflinklink
  • J. Luo and K. Hauser. Robust Trajectory Optimization Under Frictional Contact with Iterative Learning. Robotics: Science and Systems (RSS), July 2015. pdf
  • K. Hauser. Lazy Collision Checking in Asymptotically-Optimal Motion Planning. IEEE Intl. Conference on Robotics and Automation (ICRA), May 2015. pdf
  • J. Luo and K. Hauser. An Empirical Study of Optimal Motion Planning. IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS), September 2014. pdf pdf
  • K. Hauser. Fast Interpolation and Time-Optimization with Contact. International Journal of Robotics Research (IJRR), 33(9):1231-1250, August, 2014. doi: 10.1177/0278364914527855 pdf pdf software
  • K. Hauser. Fast Interpolation and Time-Optimization on Implicit Contact Submanifolds. In proceedings of Robotics: Science and Systems (RSS), Berlin, Germany, June 2013. pdf link
  • Y. Zhang, J. Luo, and K. Hauser. Sampling-based Motion Planning With Dynamic Intermediate State Objectives: Application to Throwing. In IEEE Int'l Conference on Robotics and Automation (ICRA), Minneapolis, May 2012. pdf link
  • J. Luo and K. Hauser. Interactive Generation of Dynamically Feasible Robot Trajectories from Sketches Using Temporal Mimicking. In IEEE Int'l Conference on Robotics and Automation (ICRA), Minneapolis, May 2012. pdf link
  • K. Hauser. On Responsiveness, Safety, and Completeness in Real-Time Motion Planning. Autonomous Robots, 32(1):35-48, 2012. pdf link
  • K. Hauser. Adaptive Time Stepping in Real-Time Motion Planning. In Workshop on the Algorithmic Foundations of Robotics, Singapore, 2010. pdflink
  • K. Hauser and V. Ng-Thow-Hing. Fast Smoothing of Manipulator Trajectories using Optimal Bounded-Acceleration Shortcuts. In IEEE Intl. Conf. of Robotics and Automation (ICRA), Anchorage, USA, May 2010. pdf link

Real-time obstacle avoidance with 63 moving obstacles with unpredictable, randomized behavior but bounded velocity. Robot has bounded acceleration. Real-time motion planning with adaptive time-stepping (Adaptive) is compared with constant time-stepping (Cutoff X), and two other methods: reactive potential field (PF) [Ge and Cui, 2001] and velocity obstacles (VO) [Fiorini and Shiller, 1998].

Parabolic Path Smoother Examples (ICRA 2010)

A grasping motion before smoothing

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A grasping motion after smoothing

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A PUMA760 manipulator smoothly picking and placing cups.

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