One significant risk is the time required to work with the FPGA and IMUs to obtain accurate inputs and outputs. Calibrating these components and ensuring they correctly control the robot is a major challenge. If we fail to do this efficiently, we risk not meeting our Minimum Viable Product (MVP). To mitigate this, we are prioritizing early testing and debugging sessions to identify and resolve issues as soon as possible. Additionally, we are documenting calibration steps to streamline the process for future iterations.
We modified the design by mounting the linear actuators (LAs) directly on the wheelbase instead of using an additional layer. The extra layer added unnecessary complexity, so removing it simplifies assembly. However, this change exposes the board to potential water spills. To address this, we will reinforce the platform’s edges with a polymer sealant to prevent water from seeping into critical components.
No schedule changes were made.
PART A:
Our slope-stabilizing robot enhances workplace safety and automation by ensuring the secure transportation of goods across uneven terrain. Industries such as construction and chemical handling face significant challenges in moving materials safely, often leading to worker injuries from slips, falls, and repetitive strain. By automating these deliveries, the robot reduces physical risks while improving efficiency. Its FPGA-driven real-time stability prevents spills, minimizes human exposure to hazardous substances, and reduces the agitation of sensitive materials. Our bot not only enhances operational reliability but also contributes to safer working conditions worldwide.
Additionally, our bot plays a role in the broader trend of automation and workforce displacement. As industries worldwide integrate robotics, concerns about job loss arise. While this technology may reduce certain manual labor roles, it also creates opportunities for new technical and maintenance jobs. In hazardous industries, such as chemical transport or waste management, automation significantly reduces human exposure to dangerous materials. This improves long-term health outcomes for workers globally.
For the additional prompts, Sara was responsible for part A, while Raymond was responsible for parts B and C. This reflects equal load distribution because Sara was previously responsible for 2 prompts.