Pelle Gustafsson — accepted AI-conference papers

2026

End-Effector Cartesian Velocity Control for Redundant Loader Cranes Using Reinforcement Learning (Abstract Reprint)

Abdolreza Taheri, Amy Rankka, Pelle Gustafsson, Joni Pajarinen, Reza Ghabcheloo

AAAI 2026technical

Loader cranes with multiple actuated joints are complex systems to be operated by humans. Development of advanced assistance functions, such as end-effector velocity control in Cartesian space allows for utilizing the machine to its full speed and potential, wherein actuator limits, load balance, an

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2022

Nonlinear Model Learning for Compensation and Feedforward Control of Real-World Hydraulic Actuators Using Gaussian Processes

Abdolreza Taheri, Pelle Gustafsson, Marcus Rösth, Reza Ghabcheloo, Joni Pajarinen

RA-L 2022

This paper presents a robust machine learning framework for modeling and control of hydraulic actuators. We identify several important challenges concerning learning accurate models of the dynamics for real machines, including noise and uncertainty in state measurements, nonlinear effects, input del

Cited by 10 Source ↗Scholar ↗