Inferring geometric constraints in human demonstrations

This paper presents an approach for inferring geometric constraints in human demonstrations. In our method, geometric constraint models are built to create representations of kinematic constraints such as fixed point, axial rotation, prismatic motion, planar motion and others across multiple degrees of freedom. Our method infers geometric constraints using both kinematic and force/torque information. The approach first fits all the constraint models using kinematic information and evaluates them individually using position, force and moment criteria. Our approach does not require information about the constraint type or contact geometry; it can determine both simultaneously. We present experimental evaluations using instrumented tongs that show how constraints can be robustly inferred in recordings of human demonstrations.Comment: 2nd Conference on Robot Learning (CoRL 2018). Accepted. 14 pages, 5 figure

Characterizing Input Methods for Human-to-robot Demonstrations

Human demonstrations are important in a range of robotics applications, and are created with a variety of input methods. However, the design space for these input methods has not been extensively studied. In this paper, focusing on demonstrations of hand-scale object manipulation tasks to robot arms with two-finger grippers, we identify distinct usage paradigms in robotics that utilize human-to-robot demonstrations, extract abstract features that form a design space for input methods, and characterize existing input methods as well as a novel input method that we introduce, the instrumented tongs. We detail the design specifications for our method and present a user study that compares it against three common input methods: free-hand manipulation, kinesthetic guidance, and teleoperation. Study results show that instrumented tongs provide high quality demonstrations and a positive experience for the demonstrator while offering good correspondence to the target robot.Comment: 2019 ACM/IEEE International Conference on Human-Robot Interaction (HRI

Asymmetric Coulomb Oscillation and Giant Anisotropic Magnetoresistance in Doped Graphene Nanojunctions

We report here the charge transport behavior in graphene nanojunctions in which graphene nanodots, with relatively long relaxation time, are interfaced with ferromagnetic electrodes. Subsequently we explore the effect of substitutional doping of transition metal atoms in zigzag graphene nanodots (z-GNDs) on the charge transport under non-collinear magnetization. Only substitutional doping of transition metal atoms in z-GNDs at certain sites demonstrates the spin filtering effect with a large tunnelling magnetoresistance as high as 700%, making it actually suitable for spintronic applications. From the electrical field simulation around the junction area within the electrostatic physics model, we find that the value of electric field strength increases especially with doped graphene nanodots, as the gap between the gate electrode and tip axis is reduced from 3 nm to 1 nm. Our detailed analysis further suggests the onset of asymmetric Coulomb oscillations with varying amplitudes in graphene nanodots, on being doped with magnetic ions. Such kind of tunability in the electronic conductance can potentially be exploited in designing spintronic logic gates at nanoscale.Comment: 14 pages, 4 figure

Generalized Modified Ratio Estimator for Estimation of Finite Population Mean

A generalized modified ratio estimator is proposed for estimating the population mean using the known population parameters. It is shown that the simple random sampling without replacement sample mean, the usual ratio estimator, the linear regression estimator and all the existing modified ratio estimators are the particular cases of the proposed estimator. The bias and the mean squared error of the proposed estimator are derived and are compared with that of existing estimators. The conditions for which the proposed estimator performs better than the existing estimators are also derived. The performance of the proposed estimator is assessed with that of the existing estimators for certain natural population