Littlefield, Zakary
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Shaojun Zhu
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Kourtev, Hristiyan
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Psarakis, Zacharias
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Shome, Rahul
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Kimmel, Andrew
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
Dobson, Andrew
(Computer Science, Rutgers University, Piscataway, New Jersey, USA)
,
De Souza, Alberto F.
(Departamento de Informá)
,
Bekris, Kostas E.
(tica, Universidade Federal do Espí)
This paper studies two end-effector modalities for warehouse picking: (i) a recently developed, underactuated three-finger hand and (ii) a custom built, vacuum-based gripper. The two systems differ on how they pick objects. The first tool provides increased flexibility, while the vacuum alternative ...
This paper studies two end-effector modalities for warehouse picking: (i) a recently developed, underactuated three-finger hand and (ii) a custom built, vacuum-based gripper. The two systems differ on how they pick objects. The first tool provides increased flexibility, while the vacuum alternative is simpler and smaller. The aim is to show how the end-effector influences the success rate and speed of robotic picking. For the study, the same planning process is followed for known poses of multiple objects with different geometries and characteristics. The resulting trajectories are executed on a real system showing that, under different conditions, different types of end-effectors can be beneficial. This motivates the development of hybrid solutions.
This paper studies two end-effector modalities for warehouse picking: (i) a recently developed, underactuated three-finger hand and (ii) a custom built, vacuum-based gripper. The two systems differ on how they pick objects. The first tool provides increased flexibility, while the vacuum alternative is simpler and smaller. The aim is to show how the end-effector influences the success rate and speed of robotic picking. For the study, the same planning process is followed for known poses of multiple objects with different geometries and characteristics. The resulting trajectories are executed on a real system showing that, under different conditions, different types of end-effectors can be beneficial. This motivates the development of hybrid solutions.
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