Robotic Arm
Robotic arms are being actively researched to enhance their capabilities in diverse applications, from industrial automation to assistive technologies and space exploration. Current research emphasizes improving control algorithms (e.g., model predictive control, reinforcement learning) and developing more adaptable designs, including hybrid mechanisms and soft robotics, to handle complex tasks and interact safely with humans and unstructured environments. These advancements are driving progress in areas like human-robot collaboration, deformable object manipulation, and precise control for applications such as surgery and assistive robotics, ultimately impacting various fields through increased efficiency and improved human-machine interaction.
Papers
PokeFlex: Towards a Real-World Dataset of Deformable Objects for Robotic Manipulation
Jan Obrist, Miguel Zamora, Hehui Zheng, Juan Zarate, Robert K. Katzschmann, Stelian Coros
Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot
Adam Wolniakowski, Kanstantsin Miatliuk, Jose J. Quintana, Miguel A. Ferrer, Moises Diaz