Hi, I'm Saurabh H. Mirani

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Self-driven, quick learner, passionate roboticist with a curious mind who loves solving complex, challenging real-world problems.

About

I am a passionate and dedicated robotics researcher with extensive experience in real-time motion planning, SLAM, and AI-driven solutions. My work spans cutting-edge research and industrial innovation, integrating technologies like high-dimensional real-time motion planning, deep learning, and real-time optimization to solve complex challenges in Robotics and AI.

Currently, as a Research Engineer at LG, I lead transformative projects, including designing patented navigation strategies that outperform industry benchmarks and leveraging AI for enhanced obstacle avoidance. My prior role at Flexiv Robotics allowed me to design dynamic motion planning frameworks, model predictive control, and middleware communication bridges, pushing the boundaries of real-time robotics performance.

My academic journey includes an M.S. in Intelligent Systems, Robotics, and Control from UC San Diego, where I conducted groundbreaking research on neural motion planners, achieving significant efficiency and accuracy gains. At IIT Kharagpur, I built a strong foundation in mechanical engineering, furthering my expertise in UAV motion planning and low-cost autonomous systems.

With a proven track record of innovation and a commitment to advancing robotics through research, I aim to contribute to solving pressing challenges in Robotics and AI.

Experience

Research Engineer (Navigation)
  • Spearheaded the migration from Finite State Machine (FSM) to Hierarchical State Machine (HSM), exploiting 60% of pre-existing states to eliminate redundancies, thereby reducing code duplication and improving modular scalability
  • Engineered and patented a cutting-edge cleaning strategy for autonomous robot vacuum cleaners, outclassing competitors by increasing efficiency by 25% and setting a new industry standard
  • Leveraged AI (object detection and pose estimation) to develop advanced obstacle avoidance, cutting collision incidents by 40% for small objects such as cables and toys, usually undetected by LIDAR, enhancing navigation efficiency
  • Tools: C++, ROS
Nov 2023 - Present | Bengaluru, India
Robotics Software Engineer
  • Designed and implemented a variant of Dynamic Roadmaps, for real time motion planning under uncertainty, of a dual arm setup
  • Implemented a real time path-following model predictive controller (MPC) using GRAMPC for continuous re-planning with Dynamic Roadmaps
  • Developed and released a motion planning app consisting of optimization based motion planning algorithms like TrajOpt using OSQP, IFOPT, sampling based algorithms like RRT, RRT*, Descartes, and continuous collision detection algorithm using Bullet Physics thereby reducing the deployment time from weeks to hours
  • Used the motion planning app for applications such as deburring, polishing, wire harness assembly, and bin picking
  • Good understanding of CI/CD concepts, worked on writing docker files, improved the code coverage, involved in setting up jenkins and bitbucket pipelines and auto packaging for the motion planning app
  • Experienced in working as part of an Agile Scrum team and used Jira for bug tracking and task management
  • Tools: C++, ROS
Sep 2021 - July 2023 | Santa Clara, U.S.A
Motion Planning Intern
  • Developed MATLAB module for path planning of autonomous robotic arm of high-DOF like KUKA’s LBR iiwa
  • Executed obstacle avoidance using Gilbert–Johnson–Keerthi (GJK) distance algorithm in parallel to RRT-star path planning to reduce the time complexity. The result was a refined path easily traceable by the robotic arm
  • Tools: MATLAB, ROS
May 2018 - July 2018 | Hyderabad, India
Robotics Intern
  • Improvised the motion planning for time-optimal pick and place operation of a 6 DOF robotic manipulator
  • Worked on the gripping method and stack management for teach and repeat type application of the robot
December 2017 - January 2018 | Bangalore, India

Projects

MPNet
MPNetDetails >

A computationally efficient, learning-based neural planner for solving motion planning problems

Accomplishments
  • Combined MPNet (neural planner) and Fastron (proxy collision detection) to improve accuracy and reduce planning time
  • Used LibTorch in C++ for multi-objective optimization with joint limit, collision score and path length as objectives
  • Reduced the computation time by 50% and improved the success rate from 85% to 99%
KRSSG
RoboSoccerDetails >

Soccer playing autonomous omni drive robots for RoboCup

Accomplishments
  • Tools: AVR & ARM, SolidWorks, MATLAB & Simulink, C++, Python, ROS
  • Participated in 21st RoboCup, Japan (2017)
  • Developed a fuzzy logic tuned robust PID controller for efficient control of brushless direct current motors
  • Performed a comparative study on the variations of RRT, worked on path simplifier and velocity profiling of the path
  • Conceptualized and designed the circuits based on AVR and ARM Micro-controllers and developed communication system for minimum data loss and maximum data transfer rate
  • Developed a multi-threaded 3-tier Skills-Tactics-Plays architecture for controlling omni-directional robots using ROS
  • Designed and optimized the dribbling and kicking mechanisms using SolidWorks and MATLAB & Simulink
uav
Motion planning of autonomous UAVsDetails >

Path planning using Informed RRT*

Accomplishments
  • Tools: OMPL, FCL, Octomap, ROS, Gazebo, OpenCV
  • Obtained a multi-objective optimized path for UAV using OMPL & FCL for collision detection in cluttered environment
  • Autonomous 3D occupancy (Octomap) and collision avoidance was developed and tested on Ardupilot SITL Gazebo
  • Used cheap stereoscopic camera instead of lidar reducing the cost by 90%, where point cloud was created using OpenCV
Bio-Inspired Robotics
Bio-Inspired RoboticsDetails >

Modern legged bio-inspired jumping robot

Accomplishments
  • Tools: Python
  • Explored the design and control of a quasi direct-drive legged robot, developed hands-on skills in experimental robotics, mechanical design, and python
  • Derived the forward and inverse kinematics, developed python code to control leg pesition and execute PID and time-optimal moves
  • Explored the effect of different leg designs (size/shape, with/without series-elasticity, gearing effects)
SKALA
SKALADetails >

Autonomous stair-climbing Robot

Accomplishments
  • Tools: EEG, ROS, Raspberry Pi
  • Recipient of the Gold medal in the intra-collegiate hardware exhibition 2017 at IIT Kharagpur
  • Computer vision based target following for navigation was achieved using Kanade-Lucas tracking of Shi Tomasi corners
  • Developed EEG signal based control, voice control using CMUSphinx along with a touch interface using Raspberry Pi
Rehabilitation Robotics
Rehabilitation RoboticsDetails >

Improving the therapeutic outcome of the recuperation process of disabled patients

Accomplishments
  • Tools: AVR/Arduino (IMU,Wi-fi), C++
  • Developed an exoskeleton for the lower extremity of the human body consisting of actuators and feedback sensors
  • Fabricated a plantar system to record gait cycle data using IMUs & strain gauge and transmit in real-time over Wi-fi
Semantic SLAM
Semantic SLAMDetails >

SLAM that creates semantically meaningful maps by combining geometric and semantic information

Accomplishments
  • Tools: Python, ROS, Gazebo, PyTorch, PyMC3
  • Using YOLOv3 for object detection and semantic labelling and PoseCNN for pose estimation of the detected object
  • Using libraries like PyMC3/ParaMonte for Markov Chain Monte Carlo (MCMC) data association across keyframes
sParticle Filter SLAMr
Particle Filter SLAMDetails >

A solution for SLAM based on particle filter and occupancy grid

Accomplishments
  • Tools: Python, OpenCV
  • The solution is evaluated with real-world odometry data, indoor 2-D laser scans, and RGBD measurements from THOR, a humanoid robot with lidar and Kinect v2 installed
  • Texture mapping, wherein color points from the RGBD sensor are projected onto the occupancy grid in order to color the floor
  • It is able to estimate reliable map and robot trajectory on various dataset in reasonable time
Visual-Inertial SLAM
Visual-Inertial SLAMDetails >

Visual-inertial simultaneous localization and mapping (SLAM) using the Extended Kalman Filter

Accomplishments
  • Tools: Python, OpenCV
  • EKF equations are used with a prediction step based on SE(3) kinematics and an update step based on the stereo camera observation model to perform localization and mapping.
  • The proposed solution is evaluated with real-world measurements from an IMU and a stereo camera installed in a car.
  • It can estimate reliable maps and trajectory on various datasets in a reasonable time.
Face Recognition
Door-Key ProblemDetails >

Markov Decision Processes using Dynammic programming for the Door-Key problems

Accomplishments
  • Tools: Python, Gym AI (minigrid)
stop sign detector
Stop Sign DetectorDetails >

Detect stop signs with small amount of false positives.

Accomplishments
  • Tools: Python, OpenCV
  • A classifier that will segement the image into two parts - red and not red using Gaussian Discriminative Model
  • A detector which detects if the red part has any STOP signs based on contour
  • If a STOP sign is detected, it creates a bounding box around the STOP sign and return its co-ordinates in pixels
Path Planning
Path PlanningDetails >

Path Planning using A* and RRT

Accomplishments
  • Tools: Python, OMPL
  • Implemented and compared the performance of search-based and sampling-based motion planning algorithms on several 3-D environments.
Face Recognition
Face RecognitionDetails >

Face Recognition using Principal Component Analysis (PCA)

Accomplishments
  • Tools: Python
  • Principal component analysis (PCA) is used on a collection of face images to form a set of basis features.
  • Face images are projected onto a feature space ('face space') that best encodes the variation among known face images
  • The face space is defined by the 'eigenfaces', which are the eigenvectors of the set of faces; they do not necessarily correspond to isolated features such as eyes, ears, and noses

Publications

Design, Analysis & Prototyping of a Semi-Automated Staircase-Climbing Rehabilitation Robot
Siddhartha Jha, Himanshu Chaudhary, ... Saurabh Mirani
Proceedings of the 2018 4th International Conference on Mechatronics and Robotics Engineering

Teaching

  • UC San Diego
    • Grad TA - PSYC 60, Introduction to Statistics (Spring 2021)
    • Grad TA - CSS 1, Introductory Programming for Computational Social Science (Winter 2021)
    • Grad TA - PSYC 60, Introduction to Statistics (Fall 2020)
    • Reader - MAE 30B, Dynamics and Vibrations (Spring 2020)
  • IIT Kharagpur
    • UG TA - ME22002, Thermodynamics (Spring 2019)
  • Mentor
    • ROS Workshop (UC San Diego, Winter 2021)
    • Autonomous Robotics Workshop by IEEE (IIT Kharagpur, Fall 2016)

Skills

Languages and Softwares

Python
C++11
MATLAB
Simulink
ROS
Gazebo
RViz
Proteus
SolidWorks
Eagle

Python Libraries

NumPy
SciPy
Pandas
OpenCV
scikit-learn
matplotlib
PyTorch
Gym
CasADi
OSQP
PyBullet

C++ Libraries

Eigen
Boost
Taskflow
Fast DDS
TinyXML-2
PCL
Bullet
OMPL
OctoMap
LibTorch
OpenCV
FCL
MoveIt

Other

Git
AVR
STM ARM
Raspberry Pi
BeagleBone
Arduino

Operating Systems

Linux
Windows

Education

University of California San Diego

San Diego, United States

Degree: M.S. in Intelligent Systems, Robotics and Control
Department of Electrical and Computer Engineering
GPA: 3.87/4.0

    Relevant Courseworks:

    • Planning & Learning in Robotics
    • Sensing & Estimation in Robotics
    • Statistical Learning
    • Linear Algebra
    • Bio-inspired robotics
    • Introduction to Robotics
    • Random Processes
    • Linear Systems Theory
    • Non-Linear Systems

Indian Institute of Technology Kharagpur

Kharagpur, India

Degree: B.Tech (Hons.) in Mechanical Engineering
CGPA: 9.36/10

    Relevant Courseworks:

    • Intelligent Machines & Systems
    • Robots and Robotics
    • Soft Computing
    • Probability and Statistics
    • Embedded Systems
    • Design and Analysis of Algorithms
    • Robots and Computer Controlled Machines
    • Systems and Control
    • Neuro-Fuzzy Control

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