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SOFTGRIP

The fresh food industry is highly labour-intensive with associated costs contributing up to 50% of overall production costs.  Pressure is growing to reduce these costs and the industry is simultaneously facing major labour shortages.  So far, robotic automation for picking delicate fresh produce has been impossible, mainly due to the complex, contact-rich interactions involved in such tasks.

SOFTGRIP will deliver an innovative soft gripper solution for the autonomous picking of delicate white button mushrooms cultivated on Dutch shelves.  The versatility of the proposed solution will enable the adoption of the technology by other fresh-food industries experiencing similar stringent handling requirements such as kiwi fruit, grapes and berries.

Towards this goal, the consortium will develop:

  • A low-cost, soft robotic gripper with built-in actuation, sensing and embodied intelligence that enables reliable and efficient mushroom picking
  • Material synthesis and fabrication techniques that offer precise tuning of mechanical properties, comply with food safety standards, allow for chemical recycling and offer self-repair properties
  • A set of accelerated continuum mechanics modelling algorithms that facilitate real-time, model-based control schemes, capable of being executed by limited computational resources
  • Advanced learning capabilities for the gripper through a learning by imitation framework comprising multi-task and meta-learning techniques, so that it can be deployed with minimal programming

SOFTGRIP will enable a step-change in efficiency, helping mushroom growers cut down on costs by >30% and increase their yields by >20%, while also improving job quality in the industry.  In the long-term, it will lower the barriers of robotics deployment and open up new opportunities for the adoption of robotic solutions in the agri-food sector.

TWI Hellas is responsible for the machine vision tasks: the detection and identification of the mushrooms; and for estimating the position and orientation of the soft gripper, as well as the software integration which is implemented in ROS.

Partners: Sant’Anna School of Advanced Studies, Institute of Communication and Computer Systems, NTUA, University of Essex, TEAGASC - Agriculture and Food Development Authority, MITSUI Chemicals Europe GmbH and TWI Hellas

SOFTGRIP is funded by the European Union’s Horizon 2020 programme under the ICT call “Research and Innovation boosting promising robotics applications”.

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UA-101200094-2