# Title Team Members TA Documents Sponsor
15 Automated Pour-over Coffee Machine with Imitation Learning
Jie Wang
Jingyuan Huang
Rucheng Ke
William Qiu
Said Mikki
# RFA for Automated Pour-over Coffee Machine with Imitation Learning

# Problem

The art of pour-over coffee brewing, famous for its complex flavor and high quality, is heavily dependent on the skills and experience of a barista. This craftsmanship leads to variability in coffee quality due to human inconsistency. Additionally, it is challenging for common coffee enthusiasts to replicate professional barista techniques at home or in non-specialized settings.

# Solution Overview

We propose the development of **an intelligent Automated Pour-over Coffee Machine leveraging imitation learning algorithms**. This machine will mimic the techniques of professional baristas, ensuring consistency and high-quality in every cup. The project will involve designing a mechanical structure integrated with sensors and developing sophisticated software algorithms.

# Solution Components

## Component 1: Mechanical Design

- **Purpose:** To create a machine that can physically replicates the movements and precision of a barista.
- **Features:** An adjustable nozzle for water flow control, a mechanical arm for simulating hand movements, and a stable structure to house the coffee dripper.
- **Challenges:** Ensuring precise movement and durability of moving parts, and integrating the mechanical system with electronic controls for seamless operation.
- **Expectation:** A workable, fixed coffee machine first, then upgrade it.

## Component 2: Sensors and Data Collection

- **Purpose:** To gather precise data on barista techniques for the learning algorithm.
- **Features:** High-precision sensors capturing data on water flow, angle, speed, and trajectory during the pour-over process.
- **Challenges:** Accurately capturing the nuanced movements of a professional barista and ensuring sensor durability under varying conditions.

## Component 3: Imitation Learning Algorithm

- **Purpose:** To analyze and learn from the collected data, enabling the machine to replicate these actions.
- **Features:** Advanced algorithms processing visual and sensory data to mimic barista techniques, this requires to duplicate the state-of-the-art research result from Robotics field.
- **Challenges:** Developing an algorithm capable of adapting to different styles and ensuring it can be updated as it learns from new data.

## Optional Components:

- **Multimodal Origin Information Pre-Processing:** To adjust settings based on different coffee beans and grind sizes.
- **User Interface Design:** An intuitive interface for user customization and selection of coffee preferences.
- **ChatGPT Enhanced Custom Coffee Setting**: To make the machine more intelligent and like a human barista, SOTA artificial intelligence like LLMs should be involved to make it more a sort of an agent than a regular machine.

# Criterion for Success

- **Mechanical Precision:** The machine must accurately control water flow and replicate barista movements.
- **Algorithm Effectiveness:** The machine should consistently brew coffee that matches or surpasses the quality of a professional barista.
- **User Experience:** The interface should be user-friendly, allowing customization without overwhelming the user.
- **Reliability and Durability:** The machine should operate consistently over time with minimal maintenance.
- **Taste Test Approval:** The coffee produced must be favorably reviewed in taste tests against traditional pour-over coffee.

Augmenting AR/VR with Smell

Baoyi He, Yingying Liu, Kaiyuan Tan, Xiao Wang

Featured Project


- **Kaiyuan Tan** (kt19)

- **Baoyi He** (baoyihe2)

- **Xiao Wang** (xiaow4)

- **Yingying Liu** (yl73)


Augmenting AR/VR with Smell


Augmented Reality (AR) and Virtual Reality (VR) technologies are rapidly growing and becoming more prevalent in our daily lives. However, these technologies have not yet fully addressed the sense of smell, which is a critical aspect of human experience. The absence of scent in AR/VR experiences limits the immersive potential of these technologies, preventing users from experiencing a full sensory experience.


The solution is to augment AR/VR experiences with smell, enabling users to experience a full sensory experience. This will be achieved by incorporating hardware and software components that can simulate various scents in real-time, in response to events in the AR/VR environment. The solution will consist of a scent-emitting device and software that can track and simulate scents based on the user's location and orientation in the AR/VR environment.


The solution will consist of the following components:

- **Scent-emitting device**: This device will be designed to emit various scents in real-time. It will be portable and lightweight, making it easy for users to carry around during AR/VR experiences.

- **Scent simulation software**: This software will be designed to track the user's location and orientation in the AR/VR environment and simulate scents accordingly. The software will use various algorithms to determine the intensity and duration of scent emissions.

- **AR/VR hardware**: The solution will require AR/VR hardware to create the immersive environment. This hardware will include AR/VR headsets, controllers, and other peripherals necessary to interact with the AR/VR environment.


The success of the project will be determined by the following criteria:

- **Immersive Experience**: The solution must provide an immersive AR/VR experience that incorporates smell as a key sensory input.

- **User Acceptance**: The solution must be accepted by users, who should be able to appreciate and enjoy the experience.

- **Technical Feasibility**: The solution must be technically feasible and reliable, with a low latency and high accuracy in scent simulation.

- **Scalability**: The solution should be scalable and adaptable to different AR/VR environments and hardware configurations.

- **Safety**: The solution must be safe for users and the environment, with proper ventilation and control mechanisms to prevent any harm or discomfort caused by excessive or inappropriate scent emissions.


- Model various scenerios based on AR/VR hardware. *(Tan)*

- Design algorithms which output the intensity and duration of scents based on the constructed scenerios. *(He & Liu)*

- Merge the scene with scents smoothly. *(He & Wang & Liu)*

- Design a protable scent-emitting device. *(Wang)*

- Test using real scents, invite people to experience and adjust based on feedback. *(All)*