Here, I write out random thoughts and reflections on arbitrary topics. I try to keep my thought sequence as coordinated as I can. But that’s a feat rarely accomplished by even the most articulate writers. And in as much as I aspire to acquire the ability to articulate my thoughts into concise, crisp sentences, I am without doubt no where close to ideal. And I’m not being modest. So strap tight your seat-belt and brace yourself for an unceremonious immersion into the murky depths of my befuddled thoughts. Godspeed comrade!
- On Convex Optimization
- In this post, I talk about Convex Optimization and the various algorithms for solving Unconstrained and Constrained Convex Optimization problems.
- On Optimization
- In this post, I talk about Optimization as a problem-solving approach and the various flavors of optimization problems.
- On a Usefulness Metric for robots
- In this post, I propose the Usefulness metric; a metric for determining how useful a robot is.
- On the Psychological Significance of the Death and Resurrection – Jordan Peterson
- In this post, Dr. Peterson ponders on the psychological significance of the death and resurrection archetype. This writing originally appeared in the Times on April 1, 2018.
- On Jungian Potential
- Carl Jung’s thoughts on human potential.
- On insect navigation
- In this post, I write about the various strategies insects use to navigate to and from food sources as well as general lessons we could learn from the insect species with regards to specialization and resource efficiency.
- On the realization of the dream of domestic-assistant robots
- In this piece of writing, I deliberate on the current state of the domestic-assistant robot problem.
- On Sequential Scene Understanding and Manipulation
- In this post, I ponder over SUM, a scene understanding and manipulation algorithm developed by Chad Jenkins’ group at the Michigan Robotics Institute.
- On Semantic Robot Programming
- In this piece, I talk about the significance and modus operandi of Semantic Robot programming as well as some questions I have about it.
- On Skill Discovery through Skill Chaining
- In this post, I briefly talk about a skill discovery algorithm by Professor George Konidaris and Professor Andrew Barto and about some questions I have about this work.
- Messing with OpenAI’s Mujoco-py (Tosser robot)
- In this post, I describe what each line in the Tosser simulation example script does and show a gif of the simulation in action.
- A primer on Model Predictive Control
- This post is a primer on Model Predictive Control, its various flavors, and general advice on how to choose the MPC parameters.
- A primer on KL Divergence
- This post is a brief primer on KL Divergence. It is an answer to the first of my list of confounding questions.
- On Linear Quadratic Regulators (LQR)
- In this post, I write briefly about what LQR is and its importance in Control Theory.
- On Bayesian Optimization
- In this post, I think about the motivation, workings and implementation of Bayesian Optimization.
- On Gaussian Processes
- This is a brief post on Gaussian Processes
- On Learning to Guide Task and Motion Planning
- In this post, I deliberate on current efforts to apply learning in accelerating task and motion planning for robots. Works discussed here are mainly by MIT PhD candidate Beomjoon Kim from the Learning and Intelligent Systems Lab at MIT.
- On Combined Task and Motion Planning Through an Extensive Planner-Independent Interface Layer
- In this post, I deliberate on an approach that uses off-the-shelf task planners and motion planners to perform TAMP tasks and makes no assumptions about their implementation. This work was done by Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell and Pieter Abbeel, all from UC Berkeley’s Computer Science Division.
- Reinforcement Learning Notes
- Here, I write quick notes about RL that I find necessary to aid my understanding or to guide my thoughts about certain concepts in RL.