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This paper proposes a method for human-robot (HR) task planning, considering at the same time, the design of the workplace. A model for the representation of humans and robots as a team of active resources is proposed, while equipment such as working tables and fixtures are considered passive resources. The HR workload is structured in a three-level model. A multi-criteria decision-making framework is used for the formulation of alternative layouts and task allocations. Both analytical models and simulation are used for the estimation of the criteria values, allowing for the evaluation of the different alternatives. A software prototype has been implemented and tested in white goods and in automotive industry cases, demonstrating that the tool can identify good quality solutions in a short time frame.

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This paper discusses the design and implementation of a robotic gripper that uses compressed air to (a) orient the parts in the desired grasping position, (b) guide the parts inside a grasping mechanism and (c) feed the parts to a track conveyor with sufficient accuracy. The novelty of the approach lays in the ability to perform in-hand manipulation of the object by the gripper allowing to pick randomly placed objects that have a complex geometry. Unlike existing 'pick and place' operations which are mainly focused on flat objects that require minimal manipulation (rotation around vertical axis), the gripper can re-orient the parts itself, minimizing the robot's motion. The major components of the gripper are 3D printed, allowing fast customization for different products. The manipulation and gripping mechanisms have been inspired by an application in the consumer goods industry involving the feeding of shaver handles to an assembly machine. The findings indicate that the proposed solution can be an alternative to part-dedicated, high-cost feeding equipment that is currently used.

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