28 citations · 51 across the 6 of their papers we have counts for
6 papers
A Statistical Guarantee for Representation Transfer in Multitask Imitation Learning
Bryan Chan, Karime Pereida, James Bergstra
Transferring representation for multitask imitation learning has the potential to provide improved sample efficiency on learning new tasks, when compared to learning from scratch.…
Catch the Ball: Accurate High-Speed Motions for Mobile Manipulators via Inverse Dynamics Learning
Ke Dong, Karime Pereida, Florian Shkurti +1
Mobile manipulators consist of a mobile platform equipped with one or more robot arms and are of interest for a wide array of challenging tasks because of their extended workspace…
Adaptive Model Predictive Control for High-Accuracy Trajectory Tracking in Changing Conditions
Karime Pereida, Angela Schoellig
Robots and automated systems are increasingly being introduced to unknown and dynamic environments where they are required to handle disturbances, unmodeled dynamics, and parametri…
Transfer Learning for High-Precision Trajectory Tracking Through Adaptive Feedback and Iterative Learning
Karime Pereida, Dave Kooijman, Rikky R. P. R. Duivenvoorden +1
Robust and adaptive control strategies are needed when robots or automated systems are introduced to unknown and dynamic environments where they are required to cope with disturban…
Data-Efficient Multirobot, Multitask Transfer Learning for Trajectory Tracking
Karime Pereida, Mohamed K. Helwa, Angela P. Schoellig
Transfer learning has the potential to reduce the burden of data collection and to decrease the unavoidable risks of the training phase. In this letter, we introduce a multirobot,…
High-Precision Trajectory Tracking in Changing Environments Through Adaptive Feedback and Iterative Learning
Karime Pereida, Rikky R. P. R. Duivenvoorden, Angela P. Schoellig
As robots and other automated systems are introduced to unknown and dynamic environments, robust and adaptive control strategies are required to cope with disturbances, unmodeled d…