Project

# Title Team Members TA Documents Sponsor
28 A climbing robot for building 3d printed concrete wall
 Benhao Lu
Jianye Chen
Shenghua Ye
Zhenghao Zhang
 design_document1.pdf
proposal1.pdf
 Binbin Li
## Members:

- Jianye Chen (jianyec2)
- Zhenghao Zhang (zz84)
- Shenghua Ye (sye14)
- Benhao Lu (benhaol2)

## Project title
A climbing robot for building 3d printed concrete wall

## PROBLEM:
Current 3D printing construction, while effective in reducing construction waste and improving efficiency, faces challenges in adapting to complex architectural forms and constructing tall buildings. The existing equipment is limited in spatial adaptability, especially when dealing with the irregularities and textures of 3D printed concrete structures. The need for a versatile climbing and printing system for high-rise and complex architectural construction is a pressing issue in the construction industry.

## SOLUTION OVERVIEW:
This project proposes an innovative climbing and self-supporting 3D printing system for construction. The system comprises a versatile mobile unit, including a climbing device for adapting to complex facades and a movable support system for irregular plans. The climbing device ensures stable ascent through power-driven surface adaptation and load-bearing anchors. The support system includes telescopic rails, pulleys, lifting columns, and a robotic arm for diverse construction needs. The construction system integrates material feeding, real-time printing feedback, and precise steel bar placement. The control system, based on GPS, facilitates targeted positioning, enabling intelligent construction of complex spatial structures. Overall, this solution aims to enhance 3D printing adaptability, revolutionizing construction methods for diverse architectural forms.

## SOLUTION COMPONENTS:
The proposed solution consists of the following components:

## MOBILE SYSTEM:
Climbing and lifting device with power drive, surface climbing, and load-bearing anchor lock modules. Construction support device with telescopic rails, universal pulleys, rigid lifting columns, and a multifunctional construction robotic arm.

## CONSTRUCTION SYSTEM:
Material feeding device for adjusting material flow. Printing device for real-time feedback on additive construction accuracy. Reinforcement device for positioning and laying steel bars.

## CONTROL SYSTEM:
GPS-based control system for precise positioning and printing control.

In summary, this project aims to revolutionize 3D printing construction by providing a climbing and self-supporting printing system capable of adapting to complex architectural forms and surface textures, offering a new paradigm for industrialized building construction.

## CRITERION OF SUCCESS
1. INITIALIZATION AND PRINTING COMMAND:
Receive input for architectural details and parameters.
Perform self-checks and initiate the printing command.
2. PRINTING CONSTRUCTION EXECUTION:
Execute printing at 0-1m height with moving and printing devices.
Wait for concrete to reach the desired strength.
3. SELF-CLIMBING AND CONNECTION TO SMART FEEDING SYSTEM:
Move to the self-climbing start.
Lift to the designated position.
4. HORIZONTAL MOVEMENT AND PRINTING ADJUSTMENT:
Detect and compensate for X-Y-Z oscillations.
Use TOF camera for accuracy and adjust concrete flow.
5. TASK COMPLETION AND SELF-CLIMBING:
After printing, perform downward pressure.
Retract the horizontal movement device.
## DISTRIBUTION OF WORK
1. JIANYE CHEN: MECHANICAL DESIGN AND MANUFACTURE
a) Jianye specializes in mechanical design and manufacturing aspects of the project. b) His expertise includes creating detailed mechanical plans, prototyping, and ensuring the physical components are well-crafted.

2. ZHENGHAO ZHANG: MECHANICAL DESIGN AND MANUFACTURE
a) Zhenghao complements Jianye's skills in mechanical design and manufacture. b) Together with Jianye, they form a strong team handling the physical aspects of the project, ensuring its mechanical components are robust and functional.

3. SHENGHUA YE: PCB AND DIGITAL HARDWARE
a) Shenghua focuses on the PCB and digital hardware aspects of the project. b) His expertise includes designing and implementing the electronic components, ensuring seamless integration with the mechanical elements.

4. BENHAO LU: SOFTWARE
a) Benhao specializes in the software part related to printing. b) His role involves developing the necessary software for the printing process, optimizing functionality, and ensuring a user-friendly interface.

An Intelligent Assistant Using Sign Language

Qianzhong Chen, Howie Liu, Haina Lou, Yike Zhou

Featured Project

# TEAM MEMBERS

Qianzhong Chen (qc19)

Hanwen Liu (hanwenl4)

Haina Lou (hainal2)

Yike Zhou (yikez3)

# TITLE OF THE PROJECT

An Intelligent Assistant Using Sign Language

# PROBLEM & SOLUTION OVERVIEW

Recently, smart home accessories are more and more common in people's home. A center, which is usually a speaker with voice user interface, is needed to control private smart home accessories. But a interactive speaker may not be the most ideal for people who are hard to speak or hear. Therefore, we aim to develop a intelligent assistant using sign language, which can understand sign languages, interact with people, and act as a real assistant.

# SOLUTION COMPONENTS

## Subsystem1: 12-Degree-of-Freedom Bionic Hand System

- Two moveable joints every finger driven by 5-V servo motors

- The main parts of the hand manufactured with 3D printing

- The bionic hand is fixed on a 2-DOF electrical platform

- All of the servo motors controlled by PWM signals transmitted by STM32 micro controller

## Subsystem2: The Control System

- The controlling system consists of embedded system modules including the microcontroller, high performance edge computing platform which will be used to run dynamic gesture recognition model and more than 20 motors which can control the delicate movement of our bionic hand. It also requires a high-precision camera to capture the hand gesture of users.

## Subsystem3: Dynamic Gesture Recognition System

- A external camera capturing the shape, appearance, and motion of objective hands

- A pre-trained model to help other subsystems to figure out the meaning behind the sign language. To be more specific, at the step of objects detection, we intended to adopt YOLO algorithm as well as Mediapipe, a machine learning framework developed by Google to recognize different sign language efficiently. Considering the characteristic of dynamic gesture, we also hope to adopt 3D-CNN and RNN to build our models to better fit in the spatio-temporal features.

# CRITERION OF SUCCESS

- The bionic hand can move free and fluently as designed, all of the 12 DOFs fulfilled. The movement of single joint of the finger does not interrupt or be interrupted by other movements. The durability and reliability of the bionic hand is achieved.

- The controlling system needs to be reliable and outputs stable PWM signals to motors. The edge computing platform we choose should have high performance when running the dynamic gesture recognition model.

- Our machine could recognize different sign language immediately and react with corresponding gestures without obvious delay.

# DISTRIBUTION OF WORK

- Qianzhong Chen(ME): Mechanical design and manufacture the bionic hand; tune the linking between motors and mechanical parts; work with Haina to program on STM32 to generate PWM signals and drive motors.

- Hanwen Liu(CompE): Record gesture clips to collect enough data; test camera modules; draft reports; make schedules.

- Haina Lou(EE): Implement the embedded controlling System; program the microcontroller, AI embedded edge computing module and implement serial communication.

- Yike Zhou(EE): Accomplish object detection subsystem; Build and train the machine learning models.