Pick and place are basic operations in most robotic applications, whether in industrial setups (e.g., machine tending,
assembling or bin picking) or in a service robotic domain (e.g., agriculture or at home). In some structured scenarios and
with certain types of parts, picking and placing is a mature process. However, that is not the case when it comes to
manipulating parts with high variability or in less structured environments.
Handling systems are present in any logistics system to interface between the storage and the transportation systems. For
non-structured scenarios, picking, packing and unpacking systems do exist at laboratory level. However, they have not
reached the market yet due to factors like the lack of efficiency, robustness and flexibility of currently available manipulation
and perception technologies.
The market demands systems that allow for a reduction of costs in the supply chain, increasing the competitiveness for
manufacturers and bringing a cost reduction for consumers. Handling systems represent the highest impact in the short-tomidterm
in warehouse-based systems (mainly at order picking and distribution centres) and in intra-logistics operations in
factories and retail.
The technology gap is the lack of flexible solutions that can handle objects of variable size, shape and weight as well as
different surface properties and stiffness.
PICKPLACE proposes combining human and robot capabilities to achieve a safe, flexible, dependable and efficient hybrid
pick-and-package (PAK) solution. It includes dynamic package configuration planning, flexible grasping strategies using an
innovative multifunctional gripper, robust environment perception and mechanisms and strategies for safe human-robot
These scientific and industrial objectives are motivated by the real requirements demanded by the industry, represented in
this proposal by ULMA, System Provider, who will facilitate a realistic and relevant scenario for the validation
Fields of science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- social scienceseconomics and businessbusiness and managementcommerce
Call for proposal
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