Full-day Workshop

Topics of interest focus on the application of machine learning to solve complex planning and control problems for robot motion. Topics include (but are not limited to):

  • Task representation and classification for motion-based learning
  • Intelligent planning for complex and high dimensional environments
  • Smart sampling techniques for motion planning
  • Learning feature selection for motion-based tasks
  • Methods for incorporating learning into planning
  • Reinforcement learning of motions for robotics and dynamical systems
  • Transfer of learning and motion plans, motion-based knowledge and experience sharing among the agents
  • Intelligent methods for creating motion plans that meet dynamical constraints
  • Intelligent task planning and learning under uncertainty and disturbance
  • Adaptive motion planning for system stability
  • Adaptable heuristics for efficient motion plans
  • Motion generalization - methods that learn a subset of motions and produce plans with a higher range of motions
  • Intelligent motion planning for multi-agent systems and fleets