Bruno Lima

Universidade Federal de Alagoas, University of Salerno

Papers

Total Citations

H-Index

About

Bruno Lima is a researcher advancing the frontier of human-robot interaction, with a focus on making robotic systems more intuitive and collaborative. His work centers on two key areas: natural human-robot control through gesture recognition and assistive force control for collaborative tasks. In his most cited paper (2022, 6 citations), Lima introduced a user-oriented approach combining thin-plate splines and LRCN networks to enable seamless teleoperation via hand gestures, allowing users to intuitively control a robotic arm's position and gripper status. His earlier work (2019, 2 citations) laid the groundwork with real-time hand pose tracking and classification for natural interaction. More recently (2023, 2 citations), Lima has explored assistive force control in collaborative human-robot transportation, addressing the challenge of moving heavy or bulky objects by merging human cognitive abilities with robotic strength. These contributions demonstrate his impact in creating safer, more efficient industrial robotics applications. Lima's research is particularly notable for its practical orientation, bridging the gap between complex control algorithms and real-world usability, making him a rising voice in the field of collaborative robotics.