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Kiran Gude

Robotics Software Engineer

Roboticist with expertise in Autonomous

Navigation and Deep learning along with

extensive knowledge in Hardware/software Co-

Design.

adg215@r.postjobfree.com

+491**********

Munich, Germany

WORK EXPERIENCE

Master Thesis- R&D

BMW Group (Innovative Automation)

03/2020 - Present, Munich,Germany

Implementing 3D Visual SLAM with end to end spatial AI stack for mobile manipulator using Intel Real sense D435i RGB-D cameras.

Visual inertial odometry with Deep learning-based

features(superpoint) for robust localization & pose estimation with frontend and backend layers.

Metric semantic 3D mapping with Deep learning based semantic segmentation model for Indoor scenes.

Custom training of semantic segmentation on indoor based production plant dataset.

Contact: Lukas Burseg - adg215@r.postjobfree.com

Sofware Developer

Cisco Systems

03/2016 - 06/2018, India

Development of Board bring up and Linux device drivers for cisco ASR9x series edge router hardware platforms. Testing firmware and various network drivers for

hardware reliability and packet forwarding with other chipsets like ASIC and FPGAs etc.

Implemented Python automation framework for

hardware reliability and module testing.

Software Developer

Samsung R&D Institute,India

01/2014 - 03/2016, India

Development of board bring up for MEMS sensor

chipsets in Samsung MSMx series and Exynos-3

Qualcomm based variant model devices.

Developed Linux device drivers for sensor chipsets & designed hardware abstraction layer for all drivers. Developed deep learning-based activity classification and gesture recognition using accelerometers & gyroscope for mobile & wearables.

Design and Implemented various Sensor Fusion & sensor calibration algorithms for inertial sensors, magnetic sensors, and vision sensors.

SKILLS

C/C++ Python Robotics ROS SLAM

Computer vision Localization Motion Planning

Mapping Deep Learning PyTorch MATLAB

TensorFlow CUDA TensorRT Gazebo

Linux Kernel Embedded Systems

PROJECTS

Autonomous Smart Factory to manage autonomous

mobile robots in Warehousing. (2019)

High level: Task Management, roadmap planning, charging management, finding feasible trajectories and perception of the local environment of automated mobile robots.

Design & Implementation of low-level parts which includes EKF sensor fusion & localization, motion planning, path planning with A- star, path smoothening(Bezier splines) and obstacle avoidance . Evaluating the scaling of robots versus area of the warehouse. Computer vision-based motion planning for a mobile robot system in a dynamically changing grid

environment. (2019)

Implemented image processing algorithms to identify, localize and classify the objects in robot configuration space.

The data related to each and every object stored into a geo- localized database, which is represented as model of the environment.

sampling based motion planning RRT* algorithm is implemented and navigated to goal.

Imitation learning assisted Reinforcement learning of robot to avoid humans during its motion in human-

robot workplaces (2019)

RL Agent learns from demonstration data of crowd motion which contains annotated trajectories and smoothly avoid humans Infront of it during its navigation from one point to point. Using Unity based ML-Agents toolkit for simulation environment and also for training, learning of agent.

Implemented SLAM for mobile robot based on laser

scan sensor 2D grid environment. (2018)

Implemented ROS mapping node which builds map based on laser beam reflectance probability data of the occupancy grid. Implemented particle filter based localization algorithm to localize mobile robot inside map with odometry sensor raw data. ACHIEVEMENTS

Published a paper on “Non-immersive method of

accelerometer calibration for mobile devices” in IEEE Published a paper on “user agnostic error

compensation for MEMS magnetic sensor in handheld

devices” in IEEE.

Achievements/Tasks

Achievements/Tasks

Achievements/Tasks

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EDUCATION

Masters in Autonomous system

Technical University Berlin

09/2018 - 11/2020,

Probabilistic Robotics Applied Robotics

Deep learning &

Computer vision

Computer vision &

Multimedia Systems

Applications of Robotics

and Autonomous

Systems

Bachelors in Electronics &

Communication

Jawaharlal Nehru Technological University

India

ACHIEVEMENTS

Published a paper on “FPGA Implementation of

Canonical Signed Digit multiplier” in International Journal of Electronic and Communication Research

(IJECR) Volume 3 No: 2 (2012) PP:73-78.

Granted patent for novel method of Heart rate

measurement by fusing accelerometer sensor and

Microphone data in Samsung Research.

CERTIFICATES

Coursera:Neural Networks and Deep Learning-

Deeplearning.ai (2018)

Coursera: Convolutional Neural Networks-

Deeplearning.ai (2018)

Fundamentals of Reinforcement Learning by University of Alberta & Alberta Machine Intelligence Institute on Coursera (2019)

Reinforcement Learning: Sample-based Learning

Methods (2019)

Reinforcement Learning: Prediction and Control with Function Approximation (2019)

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

LANGUAGES

English

Full Professional Proficiency

German(A1)

Elementary Proficiency

INTERESTS

Hiking Cricket DIY Badminton

Courses

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