Shreehan Santosh Kate · Robotics Engineer

Academic Background

Education

FALL 2026 — PRESENT

Master's in Robotics Engineering

Worcester Polytechnic Institute · Worcester, MA

Incoming. Coursework planned in Robot dynamics, Robot control, and Vision-based Robotic Manipulation.

NOV 2022 — MAY 2026

B.Tech, Instrumentation & Control Engineering

National Institute of Technology, Tiruchirappalli · CGPA 8/10

NITT Undergraduate STEM Research Fellowship Awardee.

Recognition

Awards & Certifications

Award

NITT Undergraduate STEM Research Fellowship

Top Merit Award · RECAL, The Alumni Association of NIT Trichy

Awarded a research grant of ₹70,000 for a proposal on adaptive reinforcement learning for predictive control of autonomous quadrotor systems.

Certification

Reinforcement Learning

NPTEL · IIT Madras, Instructor: Dr. B. Ravindran

Certification

Drone Systems and Control

NPTEL · IISc Bangalore, Instructor: Dr. Suresh Sundaram

Research & Work

Experience

JAN 2026 — MAY 2026

Robotics Software Intern

xTerra Robotics · IIT Kanpur

Architected a joint and Cartesian impedance control framework in C++ and ROS 2 for stable posture regulation and compliant task space manipulation on a 5-DOF manipulator.
Engineered a residual based wrench estimator that maps manipulator induced forces to a floating base whole body controller to keep a quadruped stable during dynamic loco-manipulation.
Led the kinematic modeling and link length optimization of a 7-DOF redundant manipulator intended for space applications.
Verified forward and inverse kinematic correctness on a physics accurate model in MuJoCo.

View materials ↗

JAN 2026 — MAY 2026

Design and Development of a 7-DOF Redundant Robotic Manipulator

Bachelor's Thesis · NIT Trichy & xTerra Robotics · Guides: Prof. K. Srinivasan, Amritanshu Manu

Established the kinematic model of the manipulator using the Craig DH convention.
Solved a multi-objective link length optimization problem with NSGA-II, selecting the Pareto knee point design at 2.825 m reach, a 0.147 conditioning number, and a 1.455 manipulability index.
Ran singularity analysis via SVD, Cauchy-Binet sub-Jacobians, and a screw dependency framework, benchmarking elbow lock as the dominant singularity and reaching 79.9% well conditioned workspace.
Implemented the Recursive Newton-Euler Algorithm at a 5 kg payload for dynamic and static torque calculation and actuator sizing.
Built a damped least squares inverse kinematics solver with per mode adaptive Gaussian damping, reaching 100% convergence.

View materials ↗

MAY 2025 — AUG 2025

Research Intern

NIT Tiruchirappalli · Guides: Prof. K. Srinivasan, Prof. T. Shuprajhaa

Synthesized a nonlinear control law by deriving the inverse dynamics of a quadrotor UAV to cancel nonlinearities for attitude and altitude control.
Proposed a hybrid deep actor-critic reinforcement learning framework supervising an Internal Model Controller for glycemic regulation.
Applied transfer learning with a pretrained PPO agent to build an adaptive controller for glycemic levels across diverse Type-1 Diabetes patient models.

View materials ↗

MAR 2025 — JUL 2025

Project Intern

Bhatiyani Astute Intelligence Limited · Bengaluru

Prepared image and video datasets in CVAT for computer vision tasks through annotation, preprocessing, and augmentation.
Trained and fine-tuned YOLOv5 models for object detection and classification of warehouse inventory items, evaluating performance with mAP and F1-score.

View materials ↗

FEB 2024 — SEP 2025

Research Assistant

NIT Tiruchirappalli · Guides: Prof. Ramakalyan Ayyagari, Prof. Subbareddy Chitta

Developed a bio-inspired LQR tuning framework with Genetic Algorithm and Particle Swarm Optimization, reaching 10.4% faster settling time and 20% lower RMSE than analytical tuning.
Built an ANN-based autopilot architecture trained on flight data to adapt to nonlinear aircraft dynamics, cutting error by 49.8%.
Identified a linear state-space model with the N4SID algorithm and designed a PID controller for a mobile system.

View materials ↗

MAY 2024 — AUG 2024

Drone Research Intern

Indian Institute of Science, Bengaluru · Guide: Prof. Jishnu Keshavan

Designed and motion-studied a UAV docking mechanism in Fusion 360 for payload lifting in multi-drone operations.
Built an ArUco marker detection pipeline in OpenCV for precision UAV landing on moving UGV platforms.
Estimated 6-DoF camera pose with the Perspective-n-Point algorithm from 3D world and 2D image correspondences.

View materials ↗

Research Output

Publications & Conferences

Accepted

Adaptive PID Control for Quadrotor UAVs Using Feedback Linearization and Deep Reinforcement Learning

2026 IEEE North East India International Energy Conversion Conference and Exhibition (NEIICON)

Read paper ↗

Accepted

Deep Reinforcement Learning Framework for Adaptive Control of Swing-up Inverted Pendulum

5th International Conference on Emerging Electronics and Automation (ICEEA)

Read paper ↗

Published

Bio-Inspired Optimization of LQR Controllers for Feedback-Linearized Cruise Missiles

9th International Conference on Inventive Systems and Control (ICISC)

View on IEEE Xplore ↗

Selected Work

Projects

MuJoCo simulation of the Franka Emika Panda arm performing perception-guided pick and place

Active · Manipulation

Perception & Control Pipeline for Redundant Manipulators

Implemented a 6-DOF Cartesian impedance controller for compliant manipulation, reaching 3.8 mm peak and 0.14 mm steady state tracking error. Built a two-camera 3D localization pipeline for the Franka Emika Panda in MuJoCo, achieving 1.4 mm position and 0.1 degree yaw accuracy without learned models. Closed the loop with a pick and place system combining wrist camera pose refinement, damped least squares IK, and contact triggered grasping, validated across 50 randomized trials with a 100% success rate.

Block diagram of the TD3 agent tuning a PID controller with feedback linearization for the nonlinear quadrotor model

Reinforcement Learning

Adaptive Control of Quadrotor UAVs

Trained TD3 and DDPG actor critic agents to dynamically tune controller gains, with a reward function shaped on LQG cost. Demonstrated disturbance rejection under external perturbations and reached 60% lower cumulative tracking error than fixed gain PID, LQR, and LMPC baselines.

System response plots for pitch rate, angle of attack, and tail deflection of the missile autopilot

Nonlinear Control

Fuzzy-Tuned LQR for Cruise Missile Autopilot

Derived a quasi linearized fourth order inner loop model from a nonlinear longitudinal missile autopilot using feedback linearization. Designed a Mamdani Type 1 fuzzy inference system in MATLAB for online adaptation of LQR weights, improving autopilot robustness by 28.92% over offline tuning.

IK trajectory verification plots showing designed versus IK to FK tracking in X, Y, Z and position and rotation error

Dynamics

7-DOF Redundant Manipulator for Space Applications

Built the kinematic model with the Craig DH convention and optimized link lengths with NSGA-II. Computed actuator torques with the Recursive Newton-Euler Algorithm at a 5 kg payload. Solved inverse kinematics with a damped least squares solver using adaptive Gaussian damping, reaching 100% convergence.

Toolset

Skills

Robotics

Manipulator KinematicsDynamicsImpedance Control Trajectory PlanningSingularity AnalysisWhole-Body Control

Coding

MATLABPythonC++ROS 2

Frameworks

PyTorchOpenCVNumPyMuJoCo

Engineering Software

SimulinkFusion 360AutoCADGazebo

Get in Touch

Let's Connect

Reaching out about manipulation research, control systems, or WPI? Happy to talk. Best by email or LinkedIn.

shreehan1912@gmail.com LinkedIn ↗