Arindam Bhattacharjee
Papers
2
Total Citations
18
H-Index
2
About
Arindam Bhattacharjee is a researcher whose work sits at the intersection of motor control, human-robot interaction, and intelligent robotics. His primary research areas include sensorimotor control, robotic guidance for motor skill acquisition, and neural network-based robotic motion planning. Bhattacharjee’s major contributions lie in understanding how robotic guidance alters the fundamental mechanisms of human movement. His 2014 study, "Effects of robotic guidance on sensorimotor control: Planning vs. online control?" (12 citations), provides critical insight into whether robot-guided practice primarily affects movement planning or online control, a distinction with significant implications for rehabilitation robotics and skill training. In parallel, his 2016 work, "A Study of Neural Network Based Inverse Kinematics Solution for a Planar Three Joint Robot with Obstacle Avoidance" (6 citations), advances practical robotics by developing a collision-free, neural network-driven inverse kinematics solution for automatic motion planning in cluttered workspaces. This dual focus—on the human side of motor learning and the algorithmic side of robot control—positions Bhattacharjee as a researcher bridging cognitive science and engineering. His work is particularly notable for its potential to inform the design of more effective robotic rehabilitation tools and autonomous manipulators.
Research Focus
Key Achievements
Top Papers
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