MicroZed-based five-axis robotic arm Dexter

I think everyone is interested in the two robotic arms that Tony Stark made at MIT Academy in Iron Man (movie). They are called dummy and butterfinget, dummy can do anything, make coffee, clean up garbage, etc. But butterfinget even one side The Tony Stark replaced the chest reactor while recording the video. Although the film seems to be somewhat sci-fi, the development of technology is moving toward smarter progress. The development team from Haddington Dynamic introduced a five-axis trainable robotic arm named Dexter, which is aimed at individual enthusiasts and launched a $100,000 crowdfunding campaign on the crowdfunding site Kickstarter.

Figure 1 Dexter five-axis mechanical arm CAD design

Figure 1 Dexter five-axis mechanical arm CAD design

Dexter has been designing and developing for five years and has continuously improved over a dozen prototype systems. The system integrates a six-channel motor controller with five stepper motors for precise positioning and 360 degrees of freedom at the end of the arm. If you are interested in robotics, automation, 3D printing and smart home, you can do secondary development on this basis, which is a very good choice.

Figure 2 Dexter system prototype physical map

Figure 2 Dexter system prototype physical map

For Dexter, the accuracy and sensitivity of each action requires strong computing power. Therefore, the Dexter core control board is equipped with Avnet MicroZed SoM, integrated with Xilinx Zynq-7000 SoC, and transplanted Linux operating system. Think of it as a small personal computer. Moreover, the FPGA part can process thousands of digital signals per second, and its parallel processing capability is unmatched by other MCUs.

Figure 3 Haddington Dynamic customized MicroZed SoM expansion board

Figure 3 Haddington Dynamic customized MicroZed SoM expansion board

The Xilinx Zynq family of fully programmable SoCs integrates ARM processors and programmable logic (FPGA) to provide more flexible control features and more intensive computing requirements for hardware acceleration. Since its introduction, it has been welcomed by engineers both in scientific research and in practical project applications. It not only brings unprecedented high performance and flexibility to embedded system engineers, but also creates a new situation in embedded system design.

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