CRISP Teleoperated Fruit Picking Dataset


Dataset containing the demonstration data collected with a teleoperation system. The CRISP teleoperated fruit picking dataset contains real-world teleoperated demonstration recordings of teleoperated grasping and manipulation sequences. The dataset offers recordings of RGB-D, Tactile and kinematic data collected during fruit pick-and-place tasks. Our items are placed in the workspace as single or as a clutter to simulate real-world food manufacturing scenarios.

It comprehends 10 recordings for 3 different objects (Avocado, Banana, Blueberry Box) in 2 different scenarios (Single, Clutter) for a total of 60 demonstrations.

The dataset includes 6 activities:

  • move-in is the act of approaching with the arm to the item the operator wants to grasp or manipulate.
  • move-out is the opposite of the previous. It corresponds to when the robot arm is leaving the workspace, with or without the item in hand.
  • manipulate occurs during the successful and unsuccessful manoeuvres for workspace decluttering.
  • grasp corresponds to the act of performing a closure around the item. This activity terminates when the hand lifts with or without the item.
  • pick-up starts at the end of the previous. It corresponds to the act of lifting the item vertically within the workspace.
  • drop terminates all the demonstrations. It occurs after a while carrying the item. It terminates when the item gets in contact with a surface outside of the workspace.

Check the dataset page for more details.

Claudio Coppola
Claudio Coppola
Robotics And Machine Learning Scientist

Machine learning and robotics expert with experience in industry and academia applying AI and data science to transportation forecasting, manufacturing automation, robotic perception, and human-robot interaction.