Predicting Impact-Induced Joint Velocity Jumps on Kinematic-Controlled Manipulator

In order to enable on-purpose robotic impact tasks, predicting joint-velocity jumps is essential to enforce controller feasibility and hardware integrity. We observe a considerable prediction error of a commonly-used approach in robotics compared against 250 benchmark experiments with the Panda manipulator. We reduce the average prediction error by 81.98% as follows:

First, we focus on task-space equations without inverting the ill-conditioned joint-space inertia matrix.

Second, before the impact event, we compute the equivalent inertial properties of the end-effector tip considering that a high-gains (stiff) kinematic-controlled manipulator behaves like a composite-rigid body.

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@Article{	  wang2022ral,
  author	= {Wang, Yuquan and Dehio, Niels and Kheddar, Abderrahmane},
  title		= {Predicting Post-Impact Joint Velocity Jumps on Kinematics
		  Controlled Manipulators},
  year		= {2022},
  volume	= {7},
  number	= {3},
  pages		= {6226 - 6233},
  journal	= {IEEE Robotics and Automation Letters}
}