LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes

Deep neural network (DNN) architectures have been shown to outperform traditional pipelines for object segmentation and pose estimation using RGBD data, but the performance of these DNN pipelines is directly tied to how representative the training data is of the true data. Hence a key requirement for employing these methods in practice is to have a large set of labeled data for your specific robotic manipulation task, a requirement that is not generally satisfied by existing datasets. In this paper we develop a pipeline to rapidly generate high quality RGBD data with pixelwise labels and object poses. We use an RGBD camera to collect video of a scene from multiple viewpoints and leverage existing reconstruction techniques to produce a 3D dense reconstruction. We label the 3D reconstruction using a human assisted ICP-fitting of object meshes. By reprojecting the results of labeling the 3D scene we can produce labels for each RGBD image of the scene. This pipeline enabled us to collect over 1,000,000 labeled object instances in just a few days. We use this dataset to answer questions related to how much training data is required, and of what quality the data must be, to achieve high performance from a DNN architecture

Localizing external contact using proprioceptive sensors : the contact particle filter

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 61-65).In order for robots to interact safely and intelligently with their environment they must be able to reliably estimate and localize external contacts. This paper introduces the CPF, the Contact Particle Filter, which is a general algorithm for detecting and localizing external contacts on rigid body robots without the need for external sensing. The CPF finds external contact points that best explain the observed external joint torque, and returns sensible estimates even when the external torque measurement is corrupted with noise. We demonstrate the capability of the CPF in multiple scenarios. We show how it can track multiple external contacts on a simulated Atlas robot, and also perform extensive simulation and hardware experiments on a Kuka iiwa robot arm.by Lucas Manuelli.S.M

Recurrent Partial Words

Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words). Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.Comment: In Proceedings WORDS 2011, arXiv:1108.341

Labor risk sharing

Thesis: S.M., Massachusetts Institute of Technology, Department of Economics, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (page 16).In this paper we aim to test the extent of labor risk sharing exists in thai village economies. Specifically we test the null hypothesis of full risk sharing at the village level. We outline a simple planner's problem that motivates our empirical specification. Our empirical specification consists of two equations, a labor supply equation that determines how many hours you work conditional on participating in the labor market, and a selection equation which determines the probability of working positive hours. Our empirical specification allows for fixed effects that correspond to different Pareto weights for the agents. Our dataset, an unusually long panel survey spanning over 160 months conducted in 16 villages in Thailand, allows us to deal with these fixed effects. Our results lead us to reject the null of full risk sharing since non-labor income has a significant negative effect on participation. In most specifications it also has a significant but small negative effect on hours worked conditional on participation. In light of these results we reject the null of full risk sharing.by Lucas Manuelli.S.M