Rutgers Robot Learning Lab
The Robot Learning Lab at Rutgers works on machine learning problems in robotics, focusing on how robots can learn from their own experience to perform complex manipulation tasks. Research addresses challenges of acting in stochastic, unstructured environments with noisy, high-dimensional sensing.
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
A fusion prediction model of tool wear based on physical information and machine learning in five-axis milling TC4 titanium alloy
Shaoqing Qin, Lida Zhu, Yanpeng Hao +7 more
Robotics and Computer-Integrated Manufacturing · 2026
Learning passive variable impedance skills for contact-rich tasks via conservative extended dynamical systems
Pingyun Nie, Jiexin Zhang, Tianxiang Jiang +4 more
Robotics and Computer-Integrated Manufacturing · 2027
A machine learning–based tool for enhancing position accuracy in industrial robots with a reduced dataset
Giuseppe Romano, Pietro Bilancia, Alberto Locatelli +3 more
Robotics and Computer-Integrated Manufacturing · 2026
A hierarchical approach to imitation learning for manipulation tasks requiring time varying forces
Rishabh Shukla, Adithya Santhosh, Shaili Gandhi +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Generalized machine learning model for deformation prediction and compensation in robotic machining
Taehwa Hong, Gyuho Kim, Seong Hyeon Kim +1 more
Robotics and Computer-Integrated Manufacturing · 2026
What Are We Actually Benchmarking in Robot Manipulation?
Tianchong Jiang, Xiangshan Tan, Samuel Wheeler +3 more
2026