Projects
My project experience is across the fields of computer vision, designing aerial and indoor robotics software systems, planning for robotics, embedded systems, electronic design automation (EDA), mobile app development and web development. It has been acquired through working in industry, academic research, startups and through participating in numerous competitions.
| Feb 2019 - June 2020 | A Discriminative-Deliberative Framework for 6-Dof Pose Estimation Location: Search Based Planning Lab, RI, CMU Learning based discriminative 6-Dof pose estimation methods require large datasets with annotated ground truth poses. Deliberative search based perception methods like PERCH 2.0 make assumptions that limit their scalibility in 6-Dof pose estimation scenarios. In this work, we combine the two together, building on their strengths and addressing the shortcomings of each. Our MaskRCNN and PERCH 2.0 based framework achieves better accuracy than state-of-the-art purely discriminative methods and requires training only for instance segmentation. Paper : Master’s Thesis, IROS 2020 / Videos : Clip 1 / Code : GitHub Skills : C++, CUDA, Python, ROS, PCL, OpenCV, OpenGL, MPI, PyTorch, Unity |
| Sep 2019 - June 2020 | PERCH 2.0 : Large Scale Deliberative Perception on GPU Location: Search Based Planning Lab, RI, CMU Perception Via Search (PERCH) is a class of algorithms that search for the best explanation of the observed scene in a space of possible rendered scenes, thus accounting for occlusion. However these algorithms are slow, owing to their deliberative nature. In this work we redesign these algorithms in order to exploit their inherent parallel nature better on a GPU. The redesigned algorithm, PERCH 2.0, is upto a ~100X faster that its predecessor PERCH. Paper : Master’s Thesis, IROS 2020 / Videos : Clip 1 / Code : GitHub / Skills : CUDA, OpenMP, C++, Python, MPI |
| April 2014 - May 2015 | Perception for Estimating Weed Density and Controlling Herbicide Use Location: IIT Kharagpur, Kharagpur, India Optimal application of herbicide for weed eradication is both cost effective and good for the environment. In this project, I designed a 6 camera and embedded controller based system that varies herbicide output based on weed density estimation from color images, cutting chemical usage by 79.5% & achieving weeding efficiency of 90.26% Paper : Current Science 2018 / Media : Skills : C++, OpenCV, Arduino |
| May 2014 - July 2014 | Visual Odometry in Smoke Occluded Environments Location: AIR Lab, RI, CMU Presence of smoke in the environment leads to loss of color contrast, precision and saturation and hence visual odometry algorithms are unable to find distinguishing features in the image. In this project, I developed an integrated real-time image dehazing and visual odometry approach for autonomous aerial navigation on a smoke degraded shipboard which was tested on a real smoke filled shipboard dataset. Links : Report / Videos : Clip 1 Skills : C++, OpenCV, ROS |
| June 2013 - May 2015 | Evolutionary Techniques for Test Scheduling in 2D/3D Circuits Location: IIT Kharagpur Modern chips consist of 100s of cores varying in size and complexity. After manufacturing of the chip, all cores need to be tested under various constraints as fast as possible. This problem is amplified further in 3D ICs. In this work, we explore if evolutionary algorithms such as Particle Swarm Optimization can be used to schedule testing the cores in parallel and minimize test time without violating constraints. We show an improvement of 51% over the SOTA. Papers : M.Tech Dissertation, ATS 2015, VTS 2015, VDAT 2014 / Skills : C++, Digital Circuits |
