Aditya Mukherjee

KIIT University

Papers

2

Total Citations

23

H-Index

2

About

Aditya Mukherjee’s research lies at the intersection of assistive robotics, human motion analysis, and wireless communication for multi-robot systems. His most impactful contribution is a novel, marker-less gait analysis technique using the Microsoft Kinect camera, which records lower-limb joint coordinates as an alternative to traditional goniometer-based measurement. This work, published in 2018 and garnering 21 citations, offers a low-cost, accessible method for assistive robotics applications, enabling more natural human-robot interaction in rehabilitation and mobility support. Mukherjee also developed a Wi-Fi communication module for ATmega microcontroller-based mobile robots, addressing the critical need for reliable TCP/IP-based networking in cooperative autonomous navigation and formation control. While this 2017 work has received 2 citations, it demonstrates his foundational interest in scalable, real-time communication for robot swarms. Together, these papers showcase Mukherjee’s dual focus on enhancing robot perception of human movement and enabling robust inter-robot coordination—key pillars for advancing autonomous systems that work alongside people.

Research Focus

Key Achievements

2
H-Index
2
Papers
23
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Kinect Camera Based Gait Data Recording and Analysis for Assistive Robotics-An Alternative to Goniometer Based Measurement Technique
21 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: KIIT University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago