Parvathi Primilla

About

Robotics/IoT engineer who deployed a fog-enabled real-time monitoring system (edge Raspberry Pi + MQTT + cloud logging) and validated it via an IEEE-indexed publication. Strong in autonomous navigation with ROS/Gazebo, SLAM/localization, and cross-layer debugging using timing/transform-delay correlation. Extends Python computer vision pipelines (YOLO + OpenCV/Albumentations) for custom datasets and weather-specific conditions.

Experience

Education

Key Strengths

• Deployed fog-enabled IoT system with edge (Raspberry Pi) + cloud logging for low-latency reliability
• MQTT architecture decisions based on message criticality (QoS 0 telemetry vs QoS 1 alerts)
• Data-driven validation of filtering/noise reduction using raw vs filtered stream comparisons and statistical metrics
• Systematic cross-layer debugging in robotics (hardware sensors, ROS stack, SLAM/localization replay, timing correlation)
• Hands-on autonomous navigation, SLAM, sensor fusion, and Gazebo simulation experience
• Customized YOLO pipelines for domain conditions (weather-specific augmentations) without modifying core model
• End-to-end integration of ROS navigation stack (SLAM + localization + move_base) into a working autonomous system
• Methodical real-time debugging using RViz/TF inspection and component-by-component isolation
• Navigation performance tuning (gmapping/AMCL parameters, costmap resolution, inflation radius, controller frequencies) to reduce drift/oscillation
• Simulation-driven validation in Gazebo with iterative test runs to achieve reliable obstacle avoidance
• Distributed robotics/IoT communication experience across ESP32, Raspberry Pi, and cloud via MQTT

Reference Highlights

• Very good technical abilities in robotics software
• Delivered excellent projects
• Strong debugging and issue-solving
• Effective problem-solving under time/feasibility constraints
• Able to optimize robot route selection
• Able to establish priorities and communication between robots
• Communicates very well
• Easy to work with
• Works well in groups
• Engaged
• Self-learning
• Motivated
• Solid knowledge of robotics design and programming