Obstacle avoidance for DMPs is still a challenging problem. In our previous work, we proposed a framework for obstacle avoidance based on superquadric potential functions to represent volumes. In this work, we extend our previous work to include the velocity of the trajectory in the definition of the potential. Our formulations guarantee smoother behavior with respect to state-of-the-art point-like methods. Moreover, our new formulation allows to obtain a smoother behavior in proximity of the obstacle than when using a static (i.e. velocity independent) potential. We validate our framework for obstacle avoidance in a simulated multi-robot scenario and with different real robots: a pick-and-place task for an industrial manipulator and a surgical robot to show scalability; and navigation with a mobile robot in dynamic environment.

中文翻译：

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动态运动原语：使用动态势函数的体积避障

DMP 的避障仍然是一个具有挑战性的问题。在我们之前的工作中，我们提出了一个基于超二次势函数来表示体积的避障框架。在这项工作中，我们扩展了我们之前的工作，将轨迹的速度包括在潜力的定义中。我们的配方保证了与最先进的点状方法相比更平滑的行为。此外，与使用静态（即与速度无关）势能时，我们的新公式允许在障碍物附近获得更平滑的行为。我们在模拟的多机器人场景和不同的真实机器人中验证了我们的避障框架：工业机械手和手术机器人的拾放任务以显示可扩展性；和在动态环境中使用移动机器人进行导航。