Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process

Constructing a smart wheelchair on a commercially available powered wheelchair (PWC) platform avoids a host of seating, mechanical design and reliability issues but requires methods of predicting and controlling the motion of a device never intended for robotics. Analog joystick inputs are subject to black-box transformations which may produce intuitive and adaptable motion control for human operators, but complicate robotic control approaches; furthermore, installation of standard axle mounted odometers on a commercial PWC is difficult. In this work, we present an integrated hardware and software system for predicting the motion of a commercial PWC platform that does not require any physical or electronic modification of the chair beyond plugging into an industry standard auxiliary input port. This system uses an RGB-D camera and an Arduino interface board to capture motion data, including visual odometry and joystick signals, via ROS communication. Future motion is predicted using an autoregressive sparse Gaussian process model. We evaluate the proposed system on real-world short-term path prediction experiments. Experimental results demonstrate the system's efficacy when compared to a baseline neural network model.Comment: The paper has been accepted to the International Conference on Robotics and Automation (ICRA2018

Chaos-assisted two-octave-spanning microcombs

Since its invention, optical frequency comb has revolutionized a broad range of subjects from metrology to spectroscopy. The recent development of microresonator-based frequency combs (microcombs) provides a unique pathway to create frequency comb systems on a chip. Indeed, microcomb-based spectroscopy, ranging, optical synthesizer, telecommunications and astronomical calibrations have been reported recently. Critical to many of the integrated comb systems is the broad coverage of comb spectra. Here, microcombs of more than two-octave span (450 nm to 2,008 nm) is demonstrated through χ^((2)) and χ^((3)) nonlinearities in a deformed silica microcavity. The deformation lifts the circular symmetry and creates chaotic tunneling channels that enable broadband collection of intracavity emission with a single waveguide. Our demonstration introduces a new degree of freedom, cavity deformation, to the microcomb studies, and our microcomb spectral range is useful for applications in optical clock, astronomical calibration and biological imaging

A Query Language for Information Graphs

In this paper we propose a database model and query language for information retrieval systems. The information graph model and Graph Object Access Language (GOAL) allow integrated handling of data, information and knowledge along with a variety of specialized objects (e.g., for geographic or multimedia information systems). There is flexible support for hyperbases, thesauri, lexicons, and both relational and object-oriented types of DBMS applications. In this paper we give the first published account of our new, powerful model and language (GOAL), illustrate their use, and compare them with related work

LEND and Faster Algorithms for Constructing Minimal Perfect Hash Functions

The Large External object-oriented Network Database (LEND) system has been developed to provide efficient access to large collections of primitive or multimedia objects, semantic networks, thesauri, hypertexts, and information retrieval collections. An overview of LEND is given, emphasizing aspects that yield efficient operation. In particular, a new algorithm is described for quickly finding minimal perfect hash functions whose specification space is very close to the theoretical lower bound, i.e., around 2 bits per key. The various stages of processing are detailed, along with analytical and empirical results, including timing for a set of over 3.8 million keys that was processed on a NeXTstation in about 6 hours

A More Cost Effective Algorithm for Finding Perfect Hash Functions

As the use of knowledge-based systems increases, there will be a growing need for efficient artificial intelligence systems and methods to access large lexicons. In the Composite Document Expert/extended/effective Retrieval (CODER) system we have, in order to provide rapid access to data items on CD-ROM's and to terms in a lexicon built from machine readable dictionaries, investigated the construction of perfect hashing functions. We have considered algorithms reported earlier in the literature, have made numerous enhancements to them, have developed new algorithms, and here report on some of our results. This paper covers an $O(n^3)$ algorithm that has been applied to building hashing functions for a collection of 69806 words on a CD-ROM. Most recently we have developed a much better algorithm and have succeeded in finding a perfect hash function for a set of 5000 words taken from the Collins English Dictionary

Tissue-smashing based ultra-rapid extraction of chemical constituents in herbal medicines

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