Papers
18
Total Citations
298
H-Index
10
About
Sandeep Manjanna is a robotics researcher whose work sits at the intersection of autonomous systems, environmental monitoring, and multi-robot coordination. His research has made significant contributions to marine robotics, where he has developed algorithms enabling robotic systems to intelligently sample and map aquatic environments — from coral reef ecosystems to freshwater reservoirs. His most cited work, "Heterogeneous Multi-Robot System for Exploration and Strategic Water Sampling" (2018, 64 citations), exemplifies his focus on deploying teams of diverse robots to tackle complex environmental sensing tasks efficiently. Alongside this, his development of amphibious "Ninja legs" for hexapod robots (42 citations) demonstrates a strong hardware innovation thread in his research, expanding the physical domains robots can explore. Manjanna has also advanced planning and search algorithms, including multi-target rendezvous strategies and Gaussian process-driven terrain coverage, reflecting his deep engagement with adaptive, data-driven robotics. His more recent work on multi-robot orienteering and scalable spatial sampling underscores a sustained commitment to making robot teams smarter and more collaborative. Collectively, his publications have garnered over 260 citations, establishing him as a meaningful contributor to field robotics and environmental monitoring applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Ninja legs: Amphibious one degree of freedom robotic legs42 citations · 2013
- 3Multi-target rendezvous search37 citations · 2016
- 4
- 5Data-driven selective sampling for marine vehicles using multi-scale paths18 citations · 2017
- 6
- 7Using Gait Change for Terrain Sensing by Robots15 citations · 2013
- 8Scalable multirobot planning for informed spatial sampling14 citations · 2022
- 9
- 10