Jo M. P. Geraedts
Papers
10
Total Citations
298
H-Index
7
About
Jo M. P. Geraedts is a leading researcher at the intersection of robotics, manufacturing, and soft actuation. Their work spans three key areas: motion planning for redundant robots, human-robot collaboration in small- and medium-sized enterprises (SMEs), and the sensing and control of soft robotic systems. Geraedts’ major contributions include a pioneering method for planning jerk-optimized trajectories under discrete time constraints, enabling smoother and more efficient motion for redundant manufacturing robots (72 citations). In soft robotics, they developed a novel color-based proprioception technique that uses multicolor 3D printing to sense bending deformation in real time, a breakthrough for feedback control in soft actuators. Their research on reducing out-of-plane deformation in soft grippers has improved grasping stability, while their efficient Jacobian-based inverse kinematics method, enhanced by sim-to-real transfer learning (60 citations), addresses the challenge of controlling highly nonlinear soft robots. Geraedts has also advanced human-robot coproduction, proposing design methodologies tailored for SMEs to boost flexibility and agility in mass-customization environments. With over 300 total citations and a portfolio of influential papers, Geraedts is recognized for bridging theoretical robotics with practical, industry-ready solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2Towards Behavior Design of a 3D-Printed Soft Robotic Hand61 citations · 2016
- 3
- 4
- 5Color-Based Proprioception of Soft Actuators Interacting With Objects30 citations · 2019
- 6
- 7Color-Based Sensing of Bending Deformation on Soft Robots12 citations · 2018
- 8Characterizing the State of the Art of Human-Robot Coproduction3 citations · 2015
- 9Exploring human robot coproduction3 citations · 2014
- 10Sensing and Reconstruction of 3-D Deformation on Pneumatic Soft Robots2 citations · 2021