Ritika Avadhanula

Github: https://github.com/rtkartista Email: advvnp@r.postjobfree.com

LinkedIn: linkedin.com/in/ritikaavadhanula/ Mobile: +1-541******* Education

Oregon State University (OSU), Corvallis, United States September 2021 - 23 Masters of Science - Robotics

Graduate Teaching Assistant: (ME 351, ROB 421, ENGR 101) Relevant Coursework: Mobile Robotics, Robotics and Artificial Intelligence, Multiple Robot Systems, Robot Motion Planning, Robot Kinematics, and Dynamics, Multi-sensor Fusion Indian Institute Of Technology, Kharagpur, India June 2016 - 20 Bachelors of Technology (Hons.) - Aerospace Engineering Relevant Coursework: Programming for Engineers, Automatic Flight Vehicle Controls, Probability, and Statistics Thesis: Performance Optimization Of The 6DOF de-Centralized Docking Controller Using Genetic Algorithms. Skills

Languages: Python, C++, MATLAB, Embedded C

Tools: ROS, GTest, Docker, GIT, OpenCV, Point Cloud Library, Moveit, Solidworks, Eigen, IPOPT Platforms: Linux, STM32, Arduino, Raspberry, Crazyflie 2.1, Turtlebot3 Domain Skills: Navigation, Path Planning, Control Systems, Autonomous Mobile Robots, Algorithms, Localization, Computer Vision Nanodegree Certificates: Robotics Software Engineer, Sensor Fusion Engineer Relevant Experience

Student Researcher, Human Machine Teaming Lab, OSU OR, USA December 2021 - Ongoing

Exhibited the working autonomy stack on the UAV hardware for distributed reactive collision avoidance with the loco positioning system for a group of 4 UAVs in indoor cluttered environments.

Authored a literature review on existing collision avoidance algorithms for multiple UAVs running in a dynamic environment with substantial state estimation noise.

Collaborated to perform experiments and estimate the loco positioning noise in an indoor setup for testbed setup. Robotics Engineering Intern, Asensus Surgical NC, USA June 2022 - August 2022

Developed and presented a ROS2 package for an upcoming robot arm’s motion using moveit and ros_controls.

Collaborated on a proposal for the development of the arm's usability in the pre-operative surgical flow. Robotics Engineer, Sirab Technologies Pvt. Ltd. India July 2020 - July 2021

Demonstrated a platooning package in ROS for an autonomous vehicle with a higher-level motion commander and a low-level model predictive controller.

Designed a monte-carlo localization package for an IMU and Radar-based vehicle localization.

Collaborated on a state machine design proposal for a truck platooning use case. Projects

Multiple Sensor Fusion for Self-driving Cars: Link1 Link2

Developed a time to collide (TTC) by fusing 2-dimensional keypoints from camera images and lidar point clouds in C++.

Formulated a vehicle detector employing an unscented Kalman filter on lidar and radar data in PCL.

Filtering, segmentation, and clustering were performed on the data obtained from the lidar scans. Autonomy on Turtlebot3: Link1 Link2

Simulated a real-time appearance-based SLAM, pick-up, and drop-off on a custom robot in ROS using move_base package.

Implemented monte-carlo localization, occupancy grid mapping, and artificial potential field planner from scratch.

Employed buffered Voronoi collision avoidance algorithm on the turtlebot3 hardware. Deep Q Learning-Based Robot Exploration: Report

Presented a 100 times faster alternative to Dijkstra’s search in python using experience replay buffers as an input to the deep Q network (DQN).

Image Segmentation: Report

Demonstrated that real-time appearance-based SLAM and holistically edge detector detects vineyard branches better than lucas-kanade optical flow on a lab setup.

Braille Generator: Link

Built a working model of a braille character generator with inverse kinematics on a robot arm hardware.