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By Theodor Borangiu

This quantity comprises the complaints of the 24th overseas convention on Robotics in Alpe-Adria-Danube area, RAAD 2015, which was once held in Bucharest, Romania, on might 27-29, 2015. The convention introduced jointly educational and researchers in robotics from the eleven nations affiliated to the Alpe-Adria-Danube area: Austria, Croatia, Czech Republic, Germany, Greece, Hungary, Italy, Romania, Serbia, Slovakia and Slovenia, and their around the globe partners.

According to its culture, RAAD 2015 coated all vital parts of study, improvement and innovation in robotics, together with new tendencies similar to: bio-inspired and cognitive robots, visible servoing of robotic movement, human-robot interplay, and private robots for ambient assisted living.

The authorised papers were grouped in 9 classes: robotic integration in commercial functions; greedy research, dexterous grippers and part layout; complex robotic movement keep watch over; robotic imaginative and prescient and sensory regulate; Human-robot interplay and collaboration; Modelling and layout of novel mechanisms and robot constructions; Robots in medication and rehabilitation; monitoring platforms and Unmanned Aerial cars; independent activity studying, movement making plans and scheduling.

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Additional info for Advances in Robot Design and Intelligent Control: Proceedings of the 24th International Conference on Robotics in Alpe-Adria-Danube Region (RAAD)

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According to [2], a solution is hybrid robot control. The next step is to implement the decision procedure in the robot controller [3], which involves both the robot and the operator. Using a virtual environment, the human’s reaction and skills can be learned [4–6]. In some cases delay problems occur [7] as a reaction of the robot positioning oscillations [8]. -P. -L. -L. ro © Springer International Publishing Switzerland 2016 T. -P. -L. Mogan 2 Assembly Methods The most efficient method of studying the assembly process is the “peg in the hole” problem.

Three different speeds for the robot were used: 10, 50 and 100 %. The mean values t and the standard deviations sd were calculated from 30 measurements (Table 1). Obviously the latency time depends on the point where the co-worker enters the collaboration zone but does not depend on the robot’s speed. 2 s. During the test sequence the robot always stopped before the co-workers hand, so that the measured difference in latency time for B1 and B2 is due to different braking ramps of the robot hardware controller.

If the hand would be defined as a collision object, the robot wouldn’t be able to reach the target position. This collaboration zone has only a certain limited height *50 mm, so that it is possible to interact with the robot. If the dimension of this zone is increased too much, it will be dangerous for the co-worker. In order to get a first indication of the latency time of only the collision detection system, the time between a trigger from the laser range finder and the complete stop of the robot was measured using internal time stamps from ROS; proximity sensors were ignored for this test.

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