Papers
18
Total Citations
249
H-Index
8
About
Praneel Chand is a robotics and artificial intelligence researcher whose work spans mobile robot navigation, multi-robot systems, and robotic arm control. His research has made meaningful contributions to some of the most challenging problems in autonomous robotics, particularly in environments where robots operate under real-world constraints such as limited memory and heterogeneous capabilities. Chand's most influential work, "Object Detection and Recognition for a Pick and Place Robot" (2014, 67 citations), demonstrates his expertise in computer vision and manipulation, developing robust image processing algorithms that enable robotic arms to identify and sort objects autonomously. His investigations into multi-robot systems — including hierarchical coordination, path planning for memory-constrained robots, and reduced human-input task allocation — reflect a sustained commitment to making robot teams more practical and scalable. His 2013 paper on heterogeneous multi-robot mapping has garnered 41 citations, underscoring the field's recognition of this work. On the manipulation side, Chand has explored neural network-based inverse kinematics and force-feedback gripper control for the SCORBOT ER-4u platform, bridging machine learning and physical robot control. With over 200 cumulative citations across his body of work, Chand has established himself as a productive contributor to applied robotics research with clear relevance to automation and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Object detection and recognition for a pick and place Robot67 citations · 2014
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- 4A two-tiered global path planning strategy for limited memory mobile robots22 citations · 2011
- 5Development of a navigation system for heterogeneous mobile robots15 citations · 2011
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- 7Applications of an adaptive hierarchical mobile robot navigation system10 citations · 2007
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