Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
👋🏼 Hello there, I'm Deep!
About me
Page not in menu
This is a page not in th emain menu
Posts
Lake Boundry Detection with Mathematica
Published:
Lake Boundry Detection with Mathematica
My friend discussed a problem he faced in finding seasonal fluctuations in water level and thus its consequences in varying lake areas and its perimeter. Given the satellite imagery of a lake, I wondered if Mathematica could solve this efficiently. I have uploaded the mathematica notebook related to it which you can find here The notebook is self-explanatory, and I have written textual arguments alongside it if someone wants to recreate it. I have tried to do it with more than one method and also put up some examples in it. Some of the pre-build functions in Mathematica do a fairly good job at it, and it is very quick to implement, but it is not super accurate. __
Automating the Flipkart Experience with Selenium
Published:
Automating Flipkart Experience with Selenium
It is not easy to encounter login issues when automating web apps, and I know it really annoying. I came across this cool method to get over such problems it requires two things that are necessary. Recently, I stumbled on undetected_chromedriver. It is a great tool to automating web apps without flagging as a bot. I tried using it alongside download site cookies, and it worked like magic! There were no bot restrictions like captcha that I came across.
You can find my code here
portfolio
LSTM-based Realtime Dst Index Predictor
Published:
publications
Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environments
Published in Robotics and Automation Letters (RA-L), 2022
The ability to autonomously navigate safely, especially within dynamic environments, is paramount for mobile robotics. In recent years, DRL approaches have shown superior performance in dynamic obstacle avoidance. However, these learning-based approaches are often developed in specially designed simulation environments and are hard to test against conventional planning approaches. Furthermore, the integration and deployment of these approaches into real robotic platforms are not yet completely solved. In this paper, we present Arena-bench, a benchmark suite to train, test, and evaluate navigation planners on different robotic platforms within 3D environments. It provides tools to design and generate highly dynamic evaluation worlds, scenarios, and tasks for autonomous navigation and is fully integrated into the robot operating system. To demonstrate the functionalities of our suite, we trained a DRL agent on our platform and compared it against a variety of existing different model-based and learning-based navigation approaches on a variety of relevant metrics. Finally, we deployed the approaches towards real robots and demonstrated the reproducibility of the results.
Recommended citation: L. Kastner et. al. (2022) "Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environments" Robotics and Automation Letters. https://arxiv.org/abs/2206.05728
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.