Integration innovativer Robotersysteme für energieeffiziente Handhabungsprozesse in der Montage
Zusammenfassung der Projektergebnisse
Within the project two prototypes for underactuated robots were realized. The SAMARA as a quasi underactuated robot with five degrees of freedom and a suction gripper was designed to perform pick and place tasks with a payload of up to 5 kg, a cycle times of lower than 2 seconds within a workspace of 1.9 meters in diameter. During the displacement phase SAMARA uses only four of its five motors to move from one point to another. The second robot is SASMo. This robot is designed using the same underactuated principle, but this time as a four degree of freedom system with only two motors and two braking systems. SASMo has a payload capability of 15 kg and is designed to be affordable priced while featuring an overall low power consumption. For both robots a new path planning was developed and tested improving on all key performance parameters. Through the used Quasi-linearization algorithm the calculation time was reduced from several hours down to some minutes with the focus on later to be implemented with real time capabilities. The difference between the simulated and real world power consumption was improved from more than 300% error to less than 20%. At the same time the speed of the systems was increased by 75% while achieving a power consumption of about 500 W on average in contrast so several kW on a comparable conventional industrial robot. Both prototypes were tested and evaluated within the testing field of the IWF.
Projektbezogene Publikationen (Auswahl)
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Effective motion design applied to energy efficient handling. PhD Thesis. Fraunhofer Verlag, 2013
Brett, T.
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Energy Efficiency Evaluation of an Underactuated Robot in Comparison to Traditional Robot Kinematics. In Procedia CIRP, 2014, 23; pp. 127–130
Glodde, A.; Afrough, M.
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Quasi-linearization Approach for the Under-actuated Robots. In: Procedia CIRP, 26, pp. 223-228, 2015
Albalasie, A; Glodde, A; Seliger, G; Abu Hanieh, A.
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Using Adaptive Model Predictive Technique to Control Under-actuated Robot and Minimize Energy Consumption. 13th Global conference on Sustainable Manufacturing, Ho Chi Minh City / Binh Duong. 16- 18 of September 2015. Elsevier, 2015
Albalasie, Ahmad; Seliger, Guenther; Abu Hanieh, Ahmed
