Author: yiluh

Yilu’s Status Report for 2/21

This week I submitted request forms for key hardware components, including the car chassis, STM32 board, and voice recognition module. All items are expected to arrive next week (definitely before spring break ends). In preparation, I reviewed implementation documentation and found a detailed online guide covering chassis assembly and motor bring-up procedures. I plan to follow these instructions and begin testing immediately once the chassis is delivered.

I also researched battery options to power the full system and identified several viable candidates that meet our voltage and current requirements. After the chassis arrives and we can verify space and load constraints, I’ll finalize the battery selection.

Additionally, our team divided responsibilities for the design report due next Friday. I will be responsible for writing the abstract and intro,  motor implementation plan, project management, ethical issues, and related work portion. Overall, progress is on schedule, and next week’s focus will be hardware bring-up and initial system testing.

Yilu’s Status Report for 2/14

This week I created a BoM for our project. Specifically, I focused on researching motor chassis options for our project to make sure we choose something that meets our load, speed, and size requirements. After comparing different platforms, we decided to use the Hiwonder Large Metal 4WD Vehicle Chassis because it supports around a 5 kg load, has suitable speed for indoor navigation, and is mechanically stable enough for our system. It’s also compatible with Raspberry Pi/stm32 control and supports encoder feedback, which will be helpful for motion control and navigation accuracy. Overall, it seems like a strong fit for both our technical needs and our integration plan.

I also worked on the design presentation slides, mainly focusing on the motor implementation section, test/verification section, and the project management portion. I outlined how we plan to wire and control the motors, what components are needed for integration, and how testing will be staged once the hardware arrives. For the planning section, I helped organize our timeline, task breakdown, and milestones so we have a clearer roadmap for the next few weeks.

Right now we’re on track with our schedule and haven’t run into any major blockers. All required components have been ordered, and once they arrive, we’ll begin testing immediately. The goal for the next phase is to verify motor control, load performance, and basic mobility before integrating sensors and camera. Really looking forward to working on the motors!

Team Status Report for 2/7

Project Overview and Scope Refinement

Based on feedback from our last meeting with Professor Tamal Mukherjee and Kyle, we refined the project scope to improve feasibility. The project was revised from an autonomous trash can designed to track and intercept trash mid-air to one that responds to voice commands and navigates to users to collect trash. This change significantly reduces mechanical and perception complexity while preserving the project’s core goals of autonomy, user interaction, and practical utility in a dorm or office environment.

Preliminary System Structure

We began outlining a high-level system architecture for the autonomous trash bin. The system will consist of sensing modules (camera, UWB, ToF), a perception layer for voice recognition and environmental understanding, a navigation and planning module for path generation and obstacle avoidance, and a low-level control layer for motor actuation. The Raspberry Pi will serve as the primary controller, coordinating sensor input, machine learning inference, and motion control.

Risk Assessment and Mitigation

Our biggest concern so far is the complexity of integrating multiple sensors, machine learning models, and control systems. Hardware incompatibilities, driver issues, or unexpected sensor behavior could slow development. To reduce this risk, we will validate each subsystem independently before full system integration. Early prototyping and staged testing will allow us to identify and resolve issues before they propagate through the system. 

Progress This Week

This week, we completed the proposal presentation slides, and Yilu delivered the presentation on Wednesday. Additionally , the team began researching machine learning models and hardware components.

  • Siying investigated candidate voice recognition and hand-detection models. 
  • Qimeng evaluated potential hardware components, including cameras, ultra-wideband (UWB) sensors, and time-of-flight (ToF) sensors. 
  • Yilu focused on identifying motors and a mobile chassis compatible with the Raspberry Pi platform.

Plans for next week

In the coming week, we plan on finalizing component selections and placing orders for required hardware. We will also complete the detailed system design, including sensor placement and control flow, and begin preparing materials for the design presentation. Initial setup and bring-up of selected components will start as soon as hardware becomes available.

Yilu’s Status Report for 2/7

This week I worked on the use case requirements, technical challenges, division of labor, and schedule sections in the presentation slides. I practiced the presentation for a few times and then carried out the speech on Wednesday (2/4). Additionally, as soon as the inventory list came out, I discussed with my teammates and reserved the Oak-D Pro Robotics Camera as our main device for depth sensing/hand detection and RPi 5 as our computation unit. I also did some research on the motor platforms that are compatible with RPi5, and found some great options. 

Our current progress aligns with the schedule. All planned milestones for this week, including proposal preparation, presentation, and early hardware planning, were completed as intended. 

In the coming week, I plan on finalizing the motor platform decision and start ordering soon after the meeting on Monday. I will also start preparing for the design presentation slides, working on finalizing the connections/protocols between different components.