Papers
8
Total Citations
75
H-Index
4
About
Anselmo Rafael Cukla is a robotics researcher whose work focuses on advancing autonomous navigation and trajectory planning for mobile and manipulator robots. His primary research areas include visual simultaneous localization and mapping (vSLAM), path planning algorithms, and sensor fusion for robotic systems. Cukla’s most influential contribution is his comparative analysis of vSLAM algorithms—ORB-SLAM2, RTAB-Map, and SPTAM—in both indoor and outdoor environments using ROS, a study that has garnered 22 citations and serves as a key reference for researchers selecting vSLAM solutions. He has also made significant strides in mobile robot navigation, with his evaluation of local trajectory planners (20 citations) and global path planners like Dijkstra and A* (18 citations) providing practical benchmarks for the robotics community. His work on sensor fusion, integrating IMU and odometry data with the AMCL algorithm, addresses critical localization challenges. Beyond mobile robotics, Cukla explores optimal trajectory planning for pneumatic manipulators, incorporating dynamical constraints and metaheuristic algorithms like firefly optimization. With over 75 total citations across his publications, Cukla’s systematic, simulation-based approach offers valuable insights for students and researchers developing robust, real-world robotic systems.
Research Focus
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Top Papers
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