Laurens Kranendonk
Papers
1
Total Citations
70
H-Index
1
About
Laurens Kranendonk is a leading researcher in human-robot interaction, with a primary focus on safe and intuitive collaboration between humans and robots in shared workspaces. His most cited work, “A Neural Network-Based Approach for Trajectory Planning in Robot–Human Handover Tasks” (2016, 70 citations), tackles a critical challenge in modern robotics: enabling robots to seamlessly and safely hand over objects to human partners. By integrating neural networks into trajectory planning, Kranendonk’s approach allows robots to predict and adapt to human motion in real time, significantly reducing collision risks and improving the fluidity of physical cooperation. This contribution has been foundational for the design of service and industrial robots that work side by side with people, addressing both safety and efficiency. His research has influenced subsequent work on sensor-based control systems and adaptive robotic behavior, helping to bridge the gap between fully automated and human-guided tasks. Kranendonk’s achievements underscore his role in advancing the next generation of collaborative robotics, where human and machine can truly work hand in hand.
Research Focus
Key Achievements
Top Papers
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