Blog Overview
This blog documents how I think and build as a robotics and AI systems engineer. It combines algorithmic depth (SLAM, sensor fusion, estimation, and learning) with practical engineering concerns such as deployment, performance, reliability, and maintainability. The posts span research-style derivations, implementation notes, and field-tested lessons from real-world robotics and perception work.
Writing Guidelines
- Choose one top-level category before publishing a post.
- Add tags that help readers discover the post from topic pages.
- Use Photo Travel for image-led travel journals and itineraries.
- Use Thoughts & Musings for reflections, essays, and personal notes.
- Prefer descriptive titles, stable slugs, and links to related earlier posts.
- For technical posts, include context, assumptions, and a clear takeaway.
Start Here
- IMU Preintegration Theory
- Sensor Fusion: Extended Kalman Filter (EKF)
- HowTo - Pose Graph Bundle Adjustment
- NetVLAD - Supervised Place Recognition
- Controlling Drone Motors
- Toy Gaussian Mixture Estimation with EM Algorithm
Blog Posts by Theme
- Robotics and Navigation: SLAM, sensor fusion, IMU preintegration, pose graph optimization, bundle adjustment
- AI and ML: deep learning, CNN, reinforcement learning, GAN
- Math and Optimization: optimization, least squares, linear algebra, probability
Tag Visualization
slam
robotics
sensor fusion
imu preintegration
optimization
deep learning
ekf
bundle adjustment
pose graph optimization
computer vision
gaussian
linear algebra
reinforcement learning
convex optimization
netvlad
drone platform
cnn
gtsam
kalman filter
all tags
Full Archive
Archive of the Blog
- Academic History: Pre University Courses, Under-Graduate Courses, Semester Wise Course, Category Wise UG Courses, PG Courses, MOOCs, TA Assignments
- Legacy Pages: Awards and Recognition, Conferences, Other Conferences, Reviewer Assignment, Miscellaneous Activities, Internships, About Me - Leisure, Photos