Team’s Status Report for 02/17/2024

We are making solid progress. This past week we focused on the overall design and algorithm implementation.

We have also solidified the design of the perception unit we plan to use.

We’ve placed order requests for the robot arm, an Ultra96v1 FPGA board, and a Kinect One camera.

We had a bit change in the division of labor — Chris will be working on dynamics and Yufei will be handling perception. Matt is currently setting up the HLS environment for the FPGA.

 

ABET responses:

A: There are many ways in which robotics can improve public health, safety, and welfare. Some of the most common applications for robotics include disaster response, search and rescue, medical robotics, and manufacturing. In all of these applications, there are scenarios where responsiveness and low latency are critical. By providing fast and efficient motion planning acceleration, our product solution aims to improve the quality of robotics in such applications. It is important to note that while accelerating motion planning is our goal, we also want to make sure that our motion planning is correct—a robot moving fast is not safe if it makes many collisions, especially when there are other people nearby. As such, it is also our responsibility to make sure that our solution is accurate with respect to a correct reference implementation of a motion planner.

B: The product solution we are designing will meet the critical demand in the automation and robotics industry — fast and efficient motion planning. This can be applied to various organizations in the manufacturing, healthcare, and logistics industries. In these industries where repetitive tasks are common, robots can take on the more physically demanding or dangerous jobs, reducing the risk of injuries and improving overall worker welfare. Hence, having accelerated accurate motion planning would further benefit the social groups working in, and are related to, these industries.

C:  Our project is centered around allowing robots to do fast and efficient motion planning.  We are specifically focusing on robotic arms with high degrees of freedom which have become ubiquitous in the manufacturing of goods.  Allowing these robots to operate more quickly and at decreased energy levels has massive economic incentives.  In theory this should decrease the cost of production for many goods as well as the price of the goods themselves.  Using our work as a backbone, robots could be trained to do even more complex tasks and work in dynamic scenarios.  This would result in the use of robots in an even wider array of applications.  An increase in robotics and automation will lead to a increase in the quality of life and a decrease in the expense of living.

A was written by Matt, B was written by Yufei, and C was written by Chris.

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