Honda Research Institute United States Inc.

Columbus, OH, United States

Honda Research Institute United States Inc.

Columbus, OH, United States
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Rao R.,Air Force Research Lab | Rao R.,Honda Research Institute United States Inc. | Liptak D.,Air Force Research Lab | Liptak D.,UES, Inc. | And 3 more authors.
Nature Materials | Year: 2012

Chiral-selective growth of single-walled carbon nanotubes (SWNTs) remains a great challenge that hinders their use in applications such as electronics and medicine. Recent experimental and theoretical reports have begun to address this problem by suggesting that selectivity may be achieved during nucleation by changing the catalyst composition or structure. Nevertheless, to establish a rational basis for chiral-selective synthesis, the underlying mechanisms governing nucleation, growth, and termination of SWNTs must be better understood. To this end, we report the first measurements of growth rates of individual SWNTs through in situ Raman spectroscopy and correlate them with their chiral angles. Our results show that the growth rates are directly proportional to the chiral angles, in agreement with recent theoretical predictions. Importantly, the evidence singles out the growth stage as responsible for the chiral distribution-distinct from nucleation and termination which might also affect the final product distribution. Our results suggest a route to chiral-selective synthesis of SWNTs through rational synthetic design strategies based on kinetic control. © 2012 Macmillan Publishers Limited. All rights reserved.

Liu Y.,Rice University | Artyukhov V.I.,Rice University | Liu M.,Rice University | Harutyunyan A.R.,Honda Research Institute United States Inc. | Yakobson B.I.,Rice University
Journal of Physical Chemistry Letters | Year: 2013

Nanomaterials are anticipated to be promising storage media, owing to their high surface-to-mass ratio. The high hydrogen capacity achieved by using graphene has reinforced this opinion and motivated investigations of the possibility to use it to store another important energy carrier - lithium (Li). While the first-principles computations show that the Li capacity of pristine graphene, limited by Li clustering and phase separation, is lower than that offered by Li intercalation in graphite, we explore the feasibility of modifying graphene for better Li storage. It is found that certain structural defects in graphene can bind Li stably, yet a more efficacious approach is through substitution doping with boron (B). In particular, the layered C3B compound stands out as a promising Li storage medium. The monolayer C 3B has a capacity of 714 mAh/g (as Li1.25C3B), and the capacity of stacked C3B is 857 mAh/g (as Li 1.5C3B), which is about twice as large as graphite's 372 mAh/g (as LiC6). Our results help clarify the mechanism of Li storage in low-dimensional materials, and shed light on the rational design of nanoarchitectures for energy storage. © 2013 American Chemical Society.

Pradeep V.,Microsoft | Lim J.,Honda Research Institute United States Inc.
International Journal of Computer Vision | Year: 2012

We propose a novel minimal solver for recovering camera motion across two views of a calibrated stereo rig. The algorithm can handle any assorted combination of point and line features across the four images and facilitates a visual odometry pipeline that is enhanced by welllocalized and reliably-tracked line features while retaining the well-known advantages of point features. The mathematical framework of our method is based on trifocal tensor geometry and a quaternion representation of rotation matrices. A simple polynomial system is developed from which camera motion parameters may be extracted more robustly in the presence of severe noise, as compared to the conventionally employed direct linear/subspace solutions. This is demonstrated with extensive experiments and comparisons against the 3-point and line-sfm algorithms. © Springer Science+Business Media, LLC 2011.

Wu T.,University of Maryland University College | Ranganathan A.,Honda Research Institute United States Inc.
IEEE Intelligent Vehicles Symposium, Proceedings | Year: 2013

Reliable lane-level localization is a requirement for many driver-assistance methods as well as for autonomous driving. Localization using cameras is desirable due to ubiquity and cheapness of sensors but is hard to achieve reliably. We propose a method towards reliable visual localization using traffic signs painted on the road such as arrows, pedestrian crossings, and speed limits. These road markings are relatively easily detected since they are designed to be highly conspicuous. Our method automatically recognizes road markings and uses features detected within them to compute the location of the vehicle. This provides an absolute global localization if the road markings have been surveyed before hand, and relative positioning information otherwise. We demonstrate using experiments and with groundtruth data that our method provides accurate lane-level visual localization under various lighting conditions and using various types of road markings. © 2013 IEEE.

Lee S.-H.,Gwangju Institute of Science and Technology | Goswami A.,Honda Research Institute United States Inc.
Autonomous Robots | Year: 2012

Recent research suggests the importance of controlling rotational dynamics of a humanoid robot in balance maintenance and gait. In this paper, we present a novel balance strategy that controls both linear and angular momentum of the robot. The controller's objective is defined in terms of the desired momenta, allowing intuitive control of the balancing behavior of the robot. By directly determining the ground reaction force (GRF) and the center of pressure (CoP) at each support foot to realize the desired momenta, this strategy can deal with non-level and nonstationary grounds, as well as different frictional properties at each foot-ground contact. When the robot cannot realize the desired values of linear and angular momenta simultaneously, the controller attributes higher priority to linear momentum at the cost of compromising angular momentum. This creates a large rotation of the upper body, reminiscent of the balancing behavior of humans. We develop a computationally efficient method to optimize GRFs and CoPs at individual foot by sequentially solving two small-scale constrained linear least-squares problems. The balance strategy is demonstrated on a simulated humanoid robot under experiments such as recovery from unknown external pushes and balancing on non-level and moving supports.

Ranganathan A.,Honda Research Institute United States Inc. | Dellaert F.,Georgia Institute of Technology
International Journal of Robotics Research | Year: 2011

We present a novel algorithm for topological mapping, which is the problem of finding the graph structure of an environment from a sequence of measurements. Our algorithm, called Online Probabilistic Topological Mapping (OPTM), systematically addresses the problem by constructing the posterior on the space of all possible topologies given measurements. With each successive measurement, the posterior is updated incrementally using a Rao-Blackwellized particle filter. We present efficient sampling mechanisms using data-driven proposals and prior distributions on topologies that further enable OPTM's operation in an online manner. OPTM can incorporate various sensors seamlessly, as is demonstrated by our use of appearance, laser, and odometry measurements. OPTM is the first topological mapping algorithm that is theoretically accurate, systematic, sensor independent, and online, and thus advances the state of the art significantly. We evaluate the algorithm on a robot in diverse environments. © 2011 The Author(s).

Paronyan T.M.,Honda Research Institute United States Inc. | Pigos E.M.,Honda Research Institute United States Inc. | Chen G.,Honda Research Institute United States Inc. | Harutyunyan A.R.,Honda Research Institute United States Inc.
ACS Nano | Year: 2011

Formation of ripples on a supported graphene sheet involves interfacial interaction with the substrate. In this work, graphene was grown on a copper foil by chemical vapor deposition from methane. On thermal quenching from elevated temperatures, we observed the formation of ripples in grown graphene, developing a peculiar topographic pattern in the form of wavy grooves and single/double rolls, roughly honeycomb cells, or their combinations. Studies on pure copper foil under corresponding conditions but without the presence of hydrocarbon revealed the appearance of peculiar patterns on the foil surface, such as dendritic structures that are distinctive not of equilibrium solidified phases but arise from planar and/or convective instabilities driven by solutal and thermal capillary forces. We propose a new origin for the formation of ripples in the course of graphene growth at elevated temperatures, where the topographic pattern formation is governed by dynamic instabilities on the interface of a carbon-catalyst binary system. These non-equilibrium processes can be described based on Mullins-Sekerka and Benard-Marangoni instabilities in diluted binary alloys, which offer control over the ripple texturing through synthesis parameters such as temperature, imposed temperature gradient, quenching rate, diffusion coefficients of carbon in the metal catalyst, and the miscibility gap of the metal catalyst-carbon system. © 2011 American Chemical Society.

Ranganathan A.,Honda Research Institute United States Inc.
Autonomous Robots | Year: 2012

A shared vocabulary between humans and robots for describing spatial concepts is essential for effective human robot interaction. Towards this goal, we present a novel technique for place categorization from visual cues called PLISS (Place Labeling through Image Sequence Segmentation). PLISS is different from existing place categorization systems in two major ways-it inherently works on video and image streams rather than single images, and it can detect "unknown" place labels, i.e. place categories that it does not know about. PLISS uses changepoint detection to temporally segment image sequences which are subsequently labeled. Changepoint detection and labeling are performed inside a systematic probabilistic framework. Unknown place labels are detected by using a probabilistic classifier and keeping track of its label uncertainty. We present experiments and comparisons on the large and extensive VPC dataset. We also demonstrate results using models learned from images downloaded from Google's image search. © 2011 Springer-Verlag.

Chen G.,Honda Research Institute United States Inc. | Paronyan T.M.,Honda Research Institute United States Inc. | Harutyunyan A.R.,Honda Research Institute United States Inc.
Applied Physics Letters | Year: 2012

Graphene is widely regarded as one of the most promising materials for sensor applications. Here, we demonstrate that a pristine graphene can detect gas molecules at extremely low concentrations with detection limits as low as 158 parts-per-quadrillion (ppq) for a range of gas molecules at room temperature. The unprecedented sensitivity was achieved by applying our recently developed concept of continuous in situ cleaning of the sensing material with ultraviolet light. The simplicity of the concept, together with graphene's flexibility to be used on various platforms, is expected to intrigue more investigations to develop ever more sensitive sensors. © 2012 American Institute of Physics.

Hauser K.,Indiana University | Ng-Thow-Hing V.,Honda Research Institute United States Inc.
International Journal of Robotics Research | Year: 2011

Robots that perform complex manipulation tasks must be able to generate strategies that make and break contact with the object. This requires reasoning in a motion space with a particular multi-modal structure, in which the state contains both a discrete mode (the contact state) and a continuous configuration (the robot and object poses). In this paper we address multi-modal motion planning in the common setting where the state is high-dimensional, and there are a continuous infinity of modes. We present a highly general algorithm, Random-MMP, that repeatedly attempts mode switches sampled at random. A major theoretical result is that Random-MMP is formally reliable and scalable, and its running time depends on certain properties of the multi-modal structure of the problem that are not explicitly dependent on dimensionality. We apply the planner to a manipulation task on the Honda humanoid robot, where the robot is asked to push an object to a desired location on a cluttered table, and the robot is restricted to switch between walking, reaching, and pushing modes. Experiments in simulation and on the real robot demonstrate that Random-MMP solves problem instances that require several carefully chosen pushes in minutes on a PC. © 2011 The Author(s).

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