Generating feasible robot motions in real-time requires achieving multiple tasks (i.e., kinematic requirements) simultaneously. These tasks can have a specific goal, a range of equally valid goals, or a range of acceptable goals with a preference toward a specific goal. To satisfy multiple and potentially competing tasks simultaneously, it is important to exploit the flexibility afforded by tasks with a range of goals. In this paper, we propose a real-time motion generation method that accommodates all three categories of tasks within a single, unified framework and leverages the flexibility of tasks with a range of goals to accommodate other tasks. Our method incorporates tasks in a weighted-sum multiple-objective optimization structure and uses barrier methods with novel loss functions to encode the valid range of a task. We demonstrate the effectiveness of our method through a simulation experiment that compares it to state-of-the-art alternative approaches, and by demonstrating it on a physical camera-in-hand robot that shows that our method enables the robot to achieve smooth and feasible camera motions.

@InProceedings{WPRG23,
  author       = "Wang, Yeping and Praveena, Pragathi and Rakita, Daniel and Gleicher, Michael",
  title        = "RangedIK: An Optimization-based Robot Motion Generation Method for Ranged-Goal Tasks",
  booktitle    = "Proceedings of the 2023 International Conference on Robotics and Automation (ICRA) ",
  year         = "2023",
  ee           = "https://ieeexplore.ieee.org/document/10161311",
  doi          = "10.1109/ICRA48891.2023.10161311",
  projecturl   = "https://github.com/uwgraphics/relaxed_ik_core",
  url          = "http://graphics.cs.wisc.edu/Papers/2023/WPRG23"
}