Sergio Caccamo
Papers
8
Total Citations
104
H-Index
6
About
Sergio Caccamo is a robotics researcher whose work sits at the intersection of autonomous exploration, 3D perception, and resilient communication for mobile robots. His most influential contributions include developing an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Fields and Gaussian Process Implicit Surfaces for active surface exploration and compact 3D reconstruction, a paper that has garnered 29 citations. He also pioneered RCAMP, a resilient communication-aware motion planner that enables mobile robots to autonomously repair wireless connectivity in the face of stochastic radio signal propagation and hardware failures (27 citations). Caccamo has made significant contributions to 3D scene understanding, including a technique for simultaneous reconstruction of static scenes and moving objects, and an unsupervised method for discovering and modeling multiple object instances from single RGB-D images. His work on teleoperation control, including adaptive object-centered control for mobile manipulators and Free Look Control for UGVs, has demonstrated enhanced performance and reduced operator workload. Additionally, he contributed the widely-used CRAWDAD dataset kth/rss, which provides RSS data collected with mobile robots in indoor and outdoor environments, serving as a valuable resource for the robotics community.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3CRAWDAD dataset kth/rss (v. 2016-01-05)16 citations · 2016
- 4Joint 3D Reconstruction of a Static Scene and Moving Objects12 citations · 2017
- 5
- 6Adaptive object centered teleoperation control of a mobile manipulator6 citations · 2016
- 7
- 8Joint 3D Reconstruction of a Static Scene and Moving Objects3 citations · 2018