Sai Praveen Daddala

Robotics and Controls Engineer | Graduate Research Assistant | Robotics Enthusiastic

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Welcome!

A small intro about me!

I am a Robotics Engineer Intern at Robossis and also currently pursuing my master's at Arizona State University in Electrical Engineering with a specialization in Robotics and Controls with a focus on hardware and software skills throughout a long journey of building personal projects, researching, and working in the industry

I am enthusiastic to work on industrial applications of autonomous cars, industrial robotics, and healthcare robotics to contribute to the global transformation being brought about by robotics and autonomous systems. I'm robotics enthusiastic and strive to acquire new skills, technology, and software in the roadmap for building a modern robot, I enjoy programming, controlling, and playing with robots.

I am currently working as a Robotics Engineer Intern in developing a next-generation robot for surgical operations, and I am also working as a Research Assistant and focus mainly on gaurantted state estimation techniques by designing an Interval Observer for Autonomous systems and Robotics.

If you are interested to discuss about Robotics and Control systems or hiring, I will be happy to connect.

🔹 Engineering Skills

Software

C++, Python, MATLAB, Simulink, ROS, RoboMaker, Linux, Gazebo, SolidWorks, Qt, AutoCAD, OpenCV, NumPy, Git, Jupiter

Hardware

Raspberry Pi, Arduino, PLC ladder logic, CAN

🔹 Experience (June 2019 - Present)

Robotics Engineer Trainee (September 2022 - Present)

Robossis, Cherry Hills, New Jersey

Working with a revolutionary three-legged surgical robot with a research team at Robossis to integrate software, hardware, and electro-mechanical components to design a Robot with Image sensing for automatic bone alignment and can also be controlled with haptics.

Graduate Research Assistant (August 2021 - Present)

Tempe, Arizona State University

Designed a Robust L1 - Interval Observer using MATLAB for highly non-linear dynamical systems for CT and DT systems and currently working on designing Interval Observer for hybrid systems

Robotics Engineer Trainee (May 2022 - July 2021)

2unify, Tempe, Arizona State University

Worked in Motion control, and testing of robotic arms on python open-source libraries like OpenCV, and NumPy for image sensing and control by collaborating with the engineering team to develop an optimized end-effector using SolidWorks.

Emerson Process Management (June 2019 - June 2020)

Chennai, India

Worked closely with industry partners by inspecting the control valves to ensure quality metrics in flow testing of valve and assisted in technical advancements of design and specifications of the control valve.

🔹 Education

Arizona State University

Master's, Electrical Engineering (Robotics and Control Systems)

CGPA: 3.9/4, Graduated: 2023

Coursework: Advanced Control Systems, Robotics, SLAM, Robot Modeling, Optimization, Artificial Neural Networks and Machine Learning

Udacity

Nano Degree, Robotics Software Engineering

Coursework: Robotics, ROS Essentials, Computer Vision, SLAM, Advanced Localization and Mapping, Path Planning

Anna University

Bachelor's Degree, Mechanical Engineering

CGPA: 3.8/4, Graduated: 2019

Coursework: Mechanical and electrical systems, Kinematics and Dynamics of Robotic, Mechatronics and Control systems

🔹 Publications

L1-Robust Interval Observer Design for Uncertain Nonlinear Dynamical Systems

Publication date: 22 June 2022

Publication Description: Institute of Electrical and Electronics Engineers (IEEE)

Google Scholar Link

State Estimation is a substantial factor in a noisy and uncertain environment while monitoring, decision-making, and control of Robotics and Autonomous Systems, hence deigning a filter to estimate state is challenging in real world. Interval Observer is designed for noisy uncertain Nonlinear Dynamical Systems without the need for additional constraints by leveraging mixed-monotone decompositions/embedding systems and minimizing the L1-gain of the observer error system. Our design offers more degrees of freedom than the majority of interval observers currently in use because it uses mixed-integer (linear) programming rather than semi-definite programs with linear matrix inequalities. It was further demonstrated that the suggested observers for both CT and DT systems were efficient and outperformed the majority of existing solutions.

🔹 Academic Projects