A robotic hand controlled by flex sensors is a project where flex sensors detect the bending or movement of fingers, allowing for the control of a robotic hand to mimic natural hand movements. 

Objectives

The primary objective of this project is to develop a robotic hand that can accurately mimic human hand movements by utilizing flex sensors to detect finger bends. By capturing and translating these bends into corresponding gestures, the project aims to achieve real-time, responsive control of the robotic hand, ensuring smooth and precise motion of each finger. The project will focus on building an affordable and functional prototype, with a strong emphasis on calibrating sensor data to enhance accuracy and proportional control. Ultimately, the goal is to create a versatile robotic hand that can be used in practical applications, such as assistive technology for individuals with limited hand function or in remote environments where direct human intervention is not feasible. 

Results

Key Achievements:

• Successfully designed a robotic hand prototype capable of performing a range of gestures.

• Achieved seamless real-time control through sensor integration.

• Demonstrated the potential for applications in prosthetics and teleoperation systems.

This project focuses on developing a robotic arm that utilizes computer vision to interact with and manipulate objects in its environment. The arm is equipped with a camera or vision sensor that captures real-time images, which are then processed using advanced image processing techniques and machine learning algorithms. The system can detect, track, and identify objects, enabling the robotic arm to make precise movements and perform tasks such as picking up, moving, or sorting objects autonomously.

The integration of vision-based control enhances the flexibility and accuracy of robotic systems, making them ideal for applications in industries such as manufacturing, healthcare, and research. The project emphasizes the combination of mechatronics and artificial intelligence to create an intelligent, adaptive robotic system that can respond dynamically to changing environments.

Key features of the project:

• Real-time object detection and tracking.

• Precision control through vision-based feedback.

• Integration of machine learning algorithms for improved decision-making.

• Applications in automation, robotics, and industrial tasks.

This project highlights the power of combining robotics and vision technologies to create smarter, more efficient systems.

The Intra-University Footboat Competition was an exhilarating event that brought together students from diverse backgrounds to showcase their skills, teamwork, and determination. As a proud member of the winning team, this competition was a memorable experience where we pushed our limits and demonstrated exceptional collaboration and strategy.

The Intra-University Footboat Competition aimed to promote teamwork, coordination, and strategic thinking among participants. It provided a platform for students to test their abilities in a challenging yet enjoyable environment, fostering both personal and group growth. Our goal as a team was to work collaboratively, remain focused under pressure, and showcase sportsmanship throughout the competition. 

Our team’s dedication and hard work paid off as we emerged as champions of the competition. Each match strengthened our bond and tested our resilience, ultimately leading us to secure the coveted title. This accomplishment not only demonstrated our teamwork and determination but also created lasting memories and a sense of pride in achieving this remarkable milestone together.