Khashayar Rohanimanesh — accepted AI-conference papers

2023

Online Tool Selection with Learned Grasp Prediction Models

Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar

ICRA 2023poster

Deep learning-based grasp prediction models have become an industry standard for robotic bin-picking systems. To maximize pick success, production environments are often equipped with several end-effector tools that can be swapped on-the-fly, based on the target object. Tool-change, however, takes t…

Cited by 1 Source ↗Scholar ↗

2018

Imitation Learning from Visual Data with Multiple Intentions

Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane +1

ICLR 2018poster

Recent advances in learning from demonstrations (LfD) with deep neural networks have enabled learning complex robot skills that involve high dimensional perception such as raw image inputs. LfD algorithms generally assume learning from single task demonstrations. In practice, however, it is more ef…

Cited by 15 Source ↗PDF ↗Scholar ↗