4 papers
LaGarNet: Goal-Conditioned Recurrent State-Space Models for Pick-and-Place Garment Flattening
Halid Abdulrahim Kadi, Kasim Terzić
We present a novel goal-conditioned recurrent state space (GC-RSSM) model capable of learning latent dynamics of pick-and-place garment manipulation. Our proposed method LaGarNet m…
Agent-Arena: A General Framework for Evaluating Control Algorithms
Halid Abdulrahim Kadi, Kasim Terzić
Robotic research is inherently challenging, requiring expertise in diverse environments and control algorithms. Adapting algorithms to new environments often poses significant diff…
DRAPER: Towards a Robust Robot Deployment and Reliable Evaluation for Quasi-Static Pick-and-Place Cloth-Shaping Neural Controllers
Halid Abdulrahim Kadi, Jose Alex Chandy, Luis Figueredo +2
Comparing robotic cloth-manipulation systems in a real-world setup is challenging. The fidelity gap between simulation-trained cloth neural controllers and real-world operation hin…
PlaNet-ClothPick: Effective Fabric Flattening Based on Latent Dynamic Planning
Halid Abdulrahim Kadi, Kasim Terzic
Why do Recurrent State Space Models such as PlaNet fail at cloth manipulation tasks? Recent work has attributed this to the blurry prediction of the observation, which makes it dif…