From 092e432180c087a42a6bad272d4723628ccde0d9 Mon Sep 17 00:00:00 2001 From: ignaciocarlucho Date: Mon, 27 Nov 2023 10:27:33 +0000 Subject: [PATCH] adding adip --- _pages/people.md | 18 ++++++++++++++++-- assets/img/profiles/adip.png | Bin 0 -> 65116 bytes 2 files changed, 16 insertions(+), 2 deletions(-) create mode 100644 assets/img/profiles/adip.png diff --git a/_pages/people.md b/_pages/people.md index 9c9348b..b9bb178 100644 --- a/_pages/people.md +++ b/_pages/people.md @@ -69,8 +69,8 @@ nav_order: 1 {% include figure.html path="assets/img/profiles/VBweb.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
- Dr. Vibhav Bharti | Personal page
- TBD
+ Dr. Vibhav Bharti | Personal page
+ Project description: It is of importance to oil and gas industry to inspect the pipelines laid down underwater for maintainance. Human efforts are not only expensive and time consuming but also there exists a chance of hazard and danger to human divers working on such tasks. Autonomous Underwater Vehicles and Remotely Operated Vehicles have shown major involvment in improving the quality of inspection over last couple of decades and reduction in human efforts. However, there are still challenges to be addressed. One such challenge that needs to be addressed is to track pipelines in and out of burial in an efficient manner. This project will investigate statistical methods to keep track of target(pipelines) using multiple sensors. Data from these sensors will be incorporated in statistical multi-sensor fusion framework using Probability Hypothesis Density (PHD) filter for having better estimates of state of the target(s).
@@ -129,6 +129,20 @@ manipulation
+ +
+
+ {% include figure.html path="assets/img/profiles/adip.png" title="example image" class="img-fluid rounded z-depth-1" %} +
+
+ Adip Das | Personal page
+ Project title: Dual-robot manipulation in industrial settings for assembly and disassembly electronic equipment and coordinated actions between human workers and robotic agents using machine learning.
+ Project description: This thesis addresses the understudied aspects of robotic assembly and disassembly in the context of the Fourth Industrial Revolution. The focus is on developing a fully autonomous system capable of efficiently performing assembly and disassembly tasks, considering the entire chain from design to reassembly. The main objective is to enhance the speed and affordability of production by implementing a vision-based robotic system for electronic equipment assembly/disassembly in industrial setups. The research aims to address uncertainties in end-of-life products without prior product-specific knowledge and explores the potential of physical human-robot collaboration in achieving economic feasibility. The project utilizes technologies for dual-robot manipulation, physical interaction, and machine-learning algorithms.
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+
+ +
+
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