Papers
10
Total Citations
106
H-Index
6
About
Rohit Menon is a robotics researcher whose work spans agricultural automation, active perception, and robotic manipulation. His most significant contributions lie at the intersection of autonomous crop monitoring and intelligent viewpoint planning, where he has developed novel approaches to address one of precision agriculture's core challenges: occlusion in complex plant environments. His landmark paper, "NBV-SC: Next Best View Planning Based on Shape Completion for Fruit Mapping and Reconstruction" (2023, 30 citations), introduced an efficient alternative to computationally expensive ray-casting methods, while his complementary work on fruit mapping with shape completion (2022, 24 citations) demonstrated how partial observations can be leveraged to accurately estimate fruit geometry and volume. His involvement in HortiBot, an adaptive multi-arm system for harvesting sweet peppers, reflects his broader ambition to translate perception advances into deployable robotic systems. Beyond agriculture, Menon has contributed to assistive robotics through semi-autonomous grasping frameworks and has explored semantic mapping, collision-aware inverse kinematics, and reinforcement learning for object placement in cluttered environments. With over 100 cumulative citations, his research consistently bridges foundational perception challenges with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Fruit Mapping with Shape Completion for Autonomous Crop Monitoring24 citations · 2022
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- 4Flexible, semi-autonomous grasping for assistive robotics12 citations · 2016
- 5Graph-Based View Motion Planning for Fruit Detection11 citations · 2023
- 6Viewpoint Push Planning for Mapping of Unknown Confined Spaces8 citations · 2023
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