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Learning To Pick Up a Novel Object

1. Abstract In order for an autonomous robot to successfully function in a natural environment it needs to be able to able to interact with objects it has never seen before. Specifically it needs to be able to manipulate objects in the environment that it has no prior knowledge of. The robot must not only be able to cope with uncertainty in the shape of the object, but also with uncertainty in the position and orientation of the object. This problem is one that can be approached with machine learning techniques. Our project is to teach a robot arm to pick up items it has never seen before. We will attempt this problem mainly with a supervised learning approach. We will train the arm by showing it a variety of objects. It will use monocular vision to extract features of the object and we will show it how to pick up the object up. Given this training set, it will learn the best way to pick up objects it has never seen before. Other work in this area includes using uncalibrated stereovision to pick up an uncertain object at Cambridge University