In modern industrial manufacturing processes, robotic manipulators are routinely used in assembly, packaging, and material handling operations. During production, changing end-of-arm tooling is frequently necessary for process flexibility and reuse of robotic resources. In conventional operation, a tool changer is sometimes employed to load and unload tools, however, the robot must be manually taught to locate the tool changers by operators via a teach pendant. During tool change teaching, the operator takes some effort and time to align the master and tool side of the coupler by adjusting the motion speed of the robotic arm and observing the alignment from different views. In this paper, a custom robotic system, the NEXUS, was programmed to locate tools automatically via an RGB-D camera. The NEXUS was configured as a multi-robot system for multiple tasks including assembly, bonding, and 3D printing of sensor arrays, solar cells, and microrobot prototypes. Thus, different tools are employed by an industrial robotic arm to position grippers, printers, and other types of end-effectors in the workspace. To improve the precision and cycle-time of the robotic tool change, we mounted an eye-in-hand RGB-D camera and employed visual servoing to accomplish the tool change process in automated mode. We then compared the teaching time of the tool location using this system and compared the cycle time with those of 6 human operators in the manual mode, including an expert user. We concluded that the tool location time in automated mode, on average, more than at least two times lower than the human operator.

Precise and Effective Robotic Tool Change Strategy Using Visual Servoing With RGB-D Camera

Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2021/volume/85369

ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2021)

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