Robin K. Singh

Robotics Engineer|

About

Welcome to my digital workspace! I'm Robin K. Singh, a robotics engineer passionate about enabling autonomous systems to operate intelligently in dynamic and unstructured environments.

I currently work at Lucid Motors as an ADAS System Integration Engineer, where I contribute to the development of in-house driving and autonomy initiatives — bridging system integration with the broader goal of delivering capable, production-ready autonomous features.

Before Lucid, I completed my M.S. in Robotics at Oregon State University, where my research focused on underwater robotic grasping — specifically, predicting and quantifying uncertainty in the motion of submerged objects under variable wave conditions, and developing dynamic grasping algorithms that adapt in real time. This work was recognized with a presentation at the IEEE OCEANS 2024 conference.

My broader expertise spans motion planning using machine learning (including sequential modeling and imitation learning), SLAM, sensor fusion, and localization for autonomous vehicles. I hold a B.Tech. in Electronics and Communication Engineering from Delhi Technological University, giving me a strong foundation across both hardware and software. Past projects include rider assistance and crash detection systems for electric motorcycles, gimbal stabilization platforms, and navigation systems for autonomous ground vehicles.

This multidisciplinary background places me at the intersection of robotics, autonomy, and system integration — and I'm always looking to push that boundary further. Feel free to connect if you'd like to collaborate or explore the future of autonomy together.

Interests

Decision Making

Data Analysis & Visualization

Algorithms

Motion Planning

Robotics

Machine Learning

Software Automation

Multiagent Systems

Education

Oregon State University

MS in Robotics

September 2022 - Present

Relevant Coursework

Machine Learning & Data Mining
Multiagent Systems
Sequential Decision Making

Delhi Technological University

B.Tech. in Electronics and Communication Engineering

August 2016 - July 2020

Relevant Coursework

Operating Systems
Microprocessors & Interfacing
Control System

Online Certification

Algorithmic Toolbox

Data Structures

Internet of Things and Embedded Systems

Experience

LUCID Motors

ADAS System Integration Er.

October 2025 - Present

Working on in-house driving/autonomy

Robotics Decision Making Laboratory (RDML)

Graduate Research Assistant (GRA)

December 2022 - March 2025 & July 2025 - October 2025

Developed a novel dynamic grasping algorithm for moving objects underwater, with simulation and scenario generation pipelines built in PyBullet and ROS 2
Trained a neural network using the ACRONYM dataset, containing 8,872 object meshes and 17.7M labeled grasp poses; transformed successful grasp trajectories into depth video sequences with stereo and IMU simulation.
Achieved up to 85% grasp success rate in high-occlusion, dynamic underwater scenarios, validating robustness of the learned policy against clutter and motion noise.

Automated Real-Time Stock Trading

September 2021 - October 2022

Built a low-latency, multi-ticker market-data pipeline (REST + sockets/WebSocket), normalized quotes/trades, and maintained rolling windows for intrabar features.
Designed signals for volume-anomaly detection and news-aware events, routing triggers to an execution engine
Implemented risk-aware execution (position limits, throttles, kill-switch) with structured logs/metrics, plus resilience via retry/backoff, watchdogs, and reconnect logic.
Optimized for constrained resources: hot-path modules in C++, orchestration/backtests in Python, lightweight manually linked executables; ran reliably on small instances (stack: Python requests/sockets, C++, Linux, pandas/NumPy, threading/async).

Yatri Motorcycles

Robotics & Automation Lead

July 2020 - July 2021

Built lane-level localization and short-horizon trajectory prediction using C++ EKF that fuses GPS and IMU; integrated the module into the ROS-based navigation stack.
Collected and curated on-road logs and Mapbox-generated simulated routes; time-synchronized and calibrated sequences, then used data-driven noise/bias modeling to tune filter parameters and improve prediction stability
Enabled reliable route-following and intent-aware planning in dense city traffic; reduced GPS-only jitter and maintained stable localization through urban-canyon segments during field testing

UNICEF Innovation Office

Feb 2018 - Apr 2019

Researcher

Worked with an international team of 12 members to develop a 1U CubeSat to study RF connection in poverty- stricken areas (predominantly Africa). Evaluated various available technologies to detect and localize radio signals from space.
Studied the feasibility of these technologies for CubeSat. In particular, space-based systems are used to analyze poverty, map schools, and perform disaster monitoring.

Nepal Telecom

May 2019 - July 2019

Student Intern

Training about the entire architecture of NTC and all technologies used by Nepal Telcom mainly focusing on GSM, wireless network systems and Optical Fiber.
Got the opportunity to work in 3 different domains namely Core, Backbone and Wireless networks under multiple mentors specializing in their respective domains.

Projects

Vision-Language Integration with OpenCV

June 2025 – July 2025

OpenCV VLM Bootcamp Project

Completed the OpenCV bootcamp on vision-language models (VLMs), focused on integrating image understanding with text-based AI systems.
Built a basic VLM application that accepts an image input and generates descriptive captions using pre-trained models.
Utilized OpenCV, PyTorch, and Hugging Face Transformers for image processing and natural language generation.
Explored attention mechanisms and multimodal embeddings to enhance the interpretability of model outputs.

F1tenth autonomous racing

Oct 2024 - March 2025

Independent Project

Uses algorithms to map the environment and track vehicle location using laser scans and odometry data.
Implements algorithms like "Follow the Gap" to navigate around static and dynamic obstacles using LiDAR data.
Utilizes RRT and RRT* to create waypoints, with Pure Pursuit for smooth trajectory following.

Calculating Option Pricing using the Black-Scholes and SABR Model

Jan 2024 - July 2024

Independent Project

Developed a comprehensive Python application for calculating option pricing using the Black-Scholes and SABR models.
Implemented Monte Carlo simulations to validate the accuracy of pricing models.
Utilized pandas for data manipulation, NumPy for numerical calculations, and Matplotlib for data visualization.
Conducted sensitivity analysis on model parameters to understand their impact on option prices.

Motion Planning using D* Lite in an Unknown Environment

Jan 2023 - Mar 2023

Associated with Oregon State University

Automated the task of pruning dormant tree branches by solving the motion planning problem of a robotic arm.
Integrated map-building with path-planning using D* Lite algorithm to navigate through dense clutter of tree branches.
Evaluated the approach using PyBullet simulator, demonstrating effective navigation and pruning.

Unmanned Ground Vehicle (UGV-DTU)

Head of Embedded Systems and Team Lead

Dec 2017 - Sep 2019

Designed and integrated GPS, IMU (Inertial Measurement Unit), LiDAR, Camera, and Encoder for vehicle localization.
Developed the vehicle's control system and power distribution circuit.
Participated in the Annual IGVC 2018 (Intelligent Ground Vehicle Competition) at Oakland University.

Team Raftaar DTU

May 2018 - June 2019

Head of Embedded Systems and Innovation

Led the electronics team in designing the data collection and display system for the vehicle.
Secured 1st prize in Innovation at ASME HPVC, issued by ASME Human Powered Vehicle Competition North America East, 2018.

Publications

Motion-Aware Underwater Robotic Grasping

Robin Kr. Singh, Geoffrey A. Hollinger

IEEE OCEANS, 2024

Grasping moving objects underwater presents unique challenges due to the unstructured environment and wave-induced oscillations, which make traditional grasping methods ineffective as objects continuously change pose, resulting in unstable grasps
The paper introduces a novel 6-DOF dynamic grasping framework that processes real-time streaming point cloud data from depth video. It tracks the object's motion and predicts its current position using a motion predictor, allowing for adaptive and confident grasp selection.
The proposed method was tested on multiple objects under three different wave conditions at the O.H. Hinsdale Wave Research Laboratory and validated in the pyBullet simulation environment, achieving an average success rate of 70% across different object configurations and conditions.

Design and modeling of novel plasmonic switches based on phase change materials

Y. Sharma, Robin Kr. Singh, S. Jain, Anuj Dhawan

Plasmonics: Design, Materials, Fabrication, Characterization, and Applications XVIII

The research introduces 2-D arrays of gold nanopillars on a gold-coated substrate, coated with vanadium dioxide (VO₂), as novel optical switches. These structures leverage plasmonic modes in the gaps between adjacent nanostructures to achieve high electromagnetic field enhancements.
By utilizing the phase transition of VO₂ from a semiconducting to a metallic state (triggered by heating or applied voltage), the plasmonic properties of the nanostructures change, leading to differential reflectance. The study employs Rigorous Coupled Wave Analysis (RCWA) to optimize the structure's switchability.
The nanostructures are demonstrated to function as optical switches with unpolarized light and can be optimized for multi-wavelength switching by introducing asymmetries in the design, such as varying gaps or periodicities in different directions.

Manned mars mission risks evaluation

Laura Bettiol, A De La Torre, D Patel, F Oluwafemi, G Kamaletdinova, ROBIN K SINGH, U Heshani, Y Lakmal, A Rivolta, A Sorokin

69th International Astronautical Congress (IAC 2018)

Mars missions can be seen as a natural step in space exploration, as Earth-like environmental conditions and the length of the interplanetary flight are the most crucial for planetary exploration compared to other celestial bodies of the Solar System. On the other hand, these missions require detailed planning and worldwide collaboration, because of the need of extremely high financial resources and technical capabilities. Many researches focused on different aspects of Mars missions are being conducted in these recent years. They include flight preparation, lift-off, interplanetary journey, habitat and Life Support Systems (LSS) design, Extravehicular Activities (EVA), precise landing, planetary exploration, etc. This paper summarizes identified safety issues that can arise during future Mars missions. Based on the analysis of previous studies, where conditions of the interplanetary flight were studied, including environmental issues, Mars habitat and the spacecraft design were discussed and the spacesuit concept was analyzed, the most critical hazards have been defined and the whole mission has been taken into consideration. In particular, possible failures and hazards for the habitat on Mars, space station and spacesuit, including off-nominal situations and their influence on the safety of the astronauts have been investigated. This work is based on the results of previous projects carried out within the Space Generation Advisory Council’s (SGAC) Space Safety and Sustainability project group, which aims to bring an international and interdisciplinary vision to this topic and discuss it from different perspectives, creating a foundation for further developments.

Skills

Programming Languages

Frameworks

Tools

Contact

My Address

Corvallis

Oregon

Social Profiles

Email

robinvishen@gmail.com

Contact

+1 503-606-6182