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Gianluca Antonelli
Researcher at University of Cassino
Publications - 215
Citations - 7015
Gianluca Antonelli is an academic researcher from University of Cassino. The author has contributed to research in topics: Mobile robot & Inverse kinematics. The author has an hindex of 41, co-authored 212 publications receiving 6054 citations. Previous affiliations of Gianluca Antonelli include University of Genoa & Technical University of Lisbon.
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Adaptive control of an autonomous underwater vehicle: experimental results on ODIN
TL;DR: The adaptive controller has been successfully implemented and experimentally validated on omnidirectional intelligent navigator (ODIN), an autonomous underwater vehicle that has been designed and built at the University of Hawaii.
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Stability Analysis for Prioritized Closed-Loop Inverse Kinematic Algorithms for Redundant Robotic Systems
TL;DR: Stability analysis of priority-based kinematic control algorithms for redundant robotic systems is approached by resorting to a Lyapunov-based stability discussion for several prioritized inverse kinematics algorithms, providing sufficient conditions for the control gains and the tasks' design for the regulation problem.
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A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking
TL;DR: This paper proposes a path following approach based on a fuzzy-logic set of rules which emulates the human driving behavior, and two completely different experiments show the effectiveness of the proposed algorithm.
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Interconnected dynamic systems: An overview on distributed control
TL;DR: Control problems such as multirobot control, distributed intelligence, swarm intelligence, distributed decision, distributed cognition, congestion control in networks, collective motion in biology, oscillator synchronization in physics, parallelization in optimization theory, distributed estimation, cooperative estimation, equilibria in economics, social interaction modeling, and game theory may be analyzed under the theory of interconnected dynamic systems.
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Kinematic Control of Platoons of Autonomous Vehicles
TL;DR: The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics and is implemented by a two-stage control architecture such that intervehicle communication is not required.