Shivam Dhakad

I’m Shivam Dhakad, a mechanical and robotics engineer with a focus on designing and prototyping real-world smart devices. My experience spans wearable rehab devices, delivery robots, and multi-DOF arms.

Skilled in CAD (SolidWorks, NX), FEA (Ansys), DFMA, and GD&T, I’ve built systems from concept to prototype using 3D printing, laser cutting, and CNC machining. I design with assembly, serviceability, and control integration in mind, ensuring performance, reliability, and manufacturability.

I thrive in fast-paced, cross-functional teams, where mechanical, electrical, and software systems come together. My goal is always to build designs that are smart, scalable, and ready for the real world.

Recent Work

Decentralized Swarm Robot Collaboration

Motion Planning: PD Controller - Robot

Publication

S. Dhakad, Design and Development of a Knee Rehabilitation Device for Hyperextension Prevention and Flexion Assistance, University of Maryland, College Park, [Technical Report], May 2025.

Projects

Knee Rehabilitation Device for Post-stroke Patients

paper, code

Developed a knee rehabilitation device to resist hyperextension and assist flexion via active and passive controllers.

Design 1: Passive controller, with Series Elastic Actuator (custom-designed torsional spring plate).

Design 2: Active Impedance PD Controller, BLDC Motor, Dynamic PD Gain Model.

Supervisor: Dr. Anindo Roy

turtlebot_perception_final_prj.mp4

Perception: Vision-Based Autonomous Navigation - TurtleBot3 Waffle

Computer Vision Stack for horizon line detection, stop sign recognition, dynamic obstacle avoidance, and path navigation.

Implemented Hough Transform for vanishing point detection, trained a YOLOv8 model for stop sign identification, utilized optical flow techniques for real-time obstacle tracking, and employed contour-based methods for waypoint detection.
ROS2 Sim & Real-World Deployment: Closed-loop control system in ROS2 Humble, integrating all four perception modules to enable real-time decision-making.
Demonstrated robust autonomous navigation with TurtleBot3 in both simulated and real-world environments, achieving seamless coordination between perception and control.

Supervisor: Prof. Dr. Samer Charifa and Dr. Tommy Chang

Mechanical Design Engineer - Delivery Vehicle

Contributed to the development of the chassis, cargo compartment, and electro-mechanical actuation assemblies.
Designed jigs and fixtures for easy manufacturing and assembly (DFMA principles).
Implemented lean manufacturing with modular design of the main robot body.

Autonomous Drill Robot for Mine Inspection

Designed a drill tower for an autonomous inspection robot that can accommodate a 1 m hammer drill rod with an interchangeable drill setup. The design is sturdy towards mobile vibrations, topple conditions, and more.

Screen-Printing Machine: Design and Kinematic Analysis

Designed a semi-automatic screen-printing machine for small-scale industrial applications, where the printing process traditionally uses a manual screen-fabric frame. Developed the machine prototype using AutoCAD for CAD modeling and validated the mechanism operations through dynamic simulation in MechDesigner software.

Designed and structurally validated (CAD|CAE) four key mechanisms; Feed rollers for sheet pickup; Screen-frame actuator for controlled printing motion; Ink spreading mechanism for uniform ink distribution; Printed sheet ejection rollers for automated paper output.
Integrated a motor assembly with a timing gearbox to synchronize mechanical operations.
Designed custom PCB circuit to enable parameter setting and system control.

Supervisor: Prof. Dr. Sunil Punjabi

Visual ArUco Marker-Based Navigation System for Mobile Robots in ROS

code

ROS-Based Autonomous Navigation: Implemented a navigation system on TurtleBot using ROS, enabling the robot to move autonomously through a predefined path.
ArUco Marker Integration: Utilized an onboard RGB camera to detect ArUco markers, which provided position-specific cues linked to parameters stored in a YAML file for guided movement.
Logical Camera Support: Integrated static logical cameras to enhance environmental perception and situational awareness, improving navigation reliability.
Modular ROS Package Development: Developed custom ROS nodes for marker detection, parameter retrieval, and navigation control using an action client, resulting in a robust, vision-guided navigation framework.

Kalman Filter: Motion Trajectory Estimation

Kalman filter implemntaion to suppresses IMU noise and drift to reconstruct accurate and stable cuboid motion trajectories. code

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