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Cooperative Localisation of a GPS-Denied UAV in 3-Dimensional Space Using Direction of Arrival Measurements

arXiv.org Artificial Intelligence

This paper presents a novel approach for localising a GPS (Global Positioning System)-denied Unmanned Aerial Vehicle (UAV) with the aid of a GPS-equipped UAV in three-dimensional space. The GPS-equipped UAV makes discrete-time broadcasts of its global coordinates. The GPS-denied UAV simultaneously receives the broadcast and takes direction of arrival (DOA) measurements towards the origin of the broadcast in its local coordinate frame (obtained via an inertial navigation system (INS)). The aim is to determine the difference between the local and global frames, described by a rotation and a translation. In the noiseless case, global coordinates were recovered exactly by solving a system of linear equations. When DOA measurements are contaminated with noise, rank relaxed semidefinite programming (SDP) and the Orthogonal Procrustes algorithm are employed. Simulations are provided and factors affecting accuracy, such as noise levels and number of measurements, are explored.


Why Cosabella replaced its agency with AI and will never go back to humans

#artificialintelligence

Headquartered in the US, with ecommerce sites in the UK, Australia, Germany, France, Italy and Canada, Cosabella decided to engage Adgorithms (the creator of Albert) out of frustration with its digital ad agency. "We know our brand best and communicating it to the advertising agency became time-consuming and difficult," Courtney Connell, marketing director of Cosabella, said, declining to name the agency as they really were "very lovely people" who she had no wish to disparage. Connell grew concerned when the retailer went through a flat quarter. "It was very scary, particularly when we enjoyed double-digit growth all the previous quarters." After parting ways with the agency, Connell looked around for alternatives and decided to try using an AI platform instead of building up a larger in-house team.


Artificial Intelligence Is Coming to Corporate Booking Tools

#artificialintelligence

Serko, a corporate travel booking and expense management business, is like a baby, Kiwi version of Concur, the SAP-owned technology company that is a developer of software that help businesses manage travel expenses. Serko's travel booking tool is used by more than 60 percent of enterprise businesses in Australia and New Zealand. The world's largest travel management companies (namely, BCD Travel, American Express Global Business Travel, Carlson Wagonlit Travel, and Hogg Robinson Group) all resell Serko's tool to their customers in Asia Pacific. So it is of regional significance that Serko plans to unveil a fresh travel-and-expense management platform with artificial intelligence (AI) baked in. In July 2017, the company will release a corporate online booking user interface as an optional premium solution alongside its booking tool for its 3 million users.


Choreographing automated cars could save time, money and lives

Robohub

If you take humans out of the driving seat, could traffic jams, accidents and high fuel bills become a thing of the past? As cars become more automated and connected, attention is turning to how to best choreograph the interaction between the tens or hundreds of automated vehicles that will one day share the same segment of Europe's road network. It is one of the most keenly studied fields in transport – how to make sure that automated cars get to their destinations safely and efficiently. But the prospect of having a multitude of vehicles taking decisions while interacting on Europe's roads is leading researchers to design new traffic management systems suitable for an era of connected transport. The idea is to ensure that traffic flows as smoothly and efficiently as possible, potentially avoiding the jams and delays caused by human behaviour.


Three years on: An update from Leka, Robot Launch winner

Robohub

Nearly three years ago, Leka won the Grand Prize at the 2014 Robot Launch competition for their robotic toy set on changing the way children with developmental disorders learn, play and progress. Leka will be the first interactive tool for children with developmental disorders that is available for direct purchase to the public. Designed for use in the home and not limited to a therapist's office, Leka enables streamlined communication between therapists, parents and children easier, more efficient and more accessible through its monitoring platform. Leka's co-founder and CEO, Ladislas de Toldi, writes about Leka's progress since the Robot Launch competition and where the company is headed in the next year. Since winning the Robot Launch competition in 2014, Leka has made immense progress and is well on it's way to getting in the hands of exceptional children around the globe.


Hey law students: Want a job? Well, you better learn to code.

Mashable

So you got into law school? Congratulations, it's time to start thinking like an engineer. Universities around the world are introducing classes that train students in the use of legal software, assisting with anything from contract creation to legal research. But are students simply training the algorithms that will take their jobs? It's increasingly clear automation won't only affect manufacturing.


Celebrate pi day with 9 trillion more digits than ever before

New Scientist

This pi day, we can write down more digits of the famous irrational number than ever before. An extra 9 trillion digits after the decimal point have been discovered, smashing the previous world record set back in 2013. In November, after 105 days of round the clock computation, pi enthusiast Peter Trueb's computer finally calculated 22,459,157,718,361 fully verified digits of pi. "I was really surprised that it worked so smoothly, I was so happy," says Trueb, who is an R&D scientist by day. Trueb realised that breaking the pi world record required two things: fast computation and fast storage.


Dive into innovation at Salesforce World Tour Sydney

#artificialintelligence

Get up close and personal with the technologies, processes and frameworks that empower and encourage innovation at Salesforce World Tour Sydney. Innovation is no longer exclusive to product or service development. It is now necessary in customer service, marketing, sales and all other departments. So what are the secrets to doing it well? From artificial intelligence to start-ups pitching for investment to the development of systems that will thrill your customers, we delve into innovation from every angle, always with a view to demystifying, informing and offering practical solutions for those in business.


On the Analysis of the DeGroot-Friedkin Model with Dynamic Relative Interaction Matrices

arXiv.org Artificial Intelligence

This paper analyses the DeGroot-Friedkin model for evolution of the individuals' social powers in a social network when the network topology varies dynamically (described by dynamic relative interaction matrices). The DeGroot-Friedkin model describes how individual social power (self-appraisal, self-weight) evolves as a network of individuals discuss a sequence of issues. We seek to study dynamically changing relative interactions because interactions may change depending on the issue being discussed. In order to explore the problem in detail, two different cases of issue-dependent network topologies are studied. First, if the topology varies between issues in a periodic manner, it is shown that the individuals' self-appraisals admit a periodic solution. Second, if the topology changes arbitrarily, under the assumption that each relative interaction matrix is doubly stochastic and irreducible, the individuals' self-appraisals asymptotically converge to a unique non-trivial equilibrium.


A Random Finite Set Model for Data Clustering

arXiv.org Machine Learning

The goal of data clustering is to partition data points into groups to minimize a given objective function. While most existing clustering algorithms treat each data point as vector, in many applications each datum is not a vector but a point pattern or a set of points. Moreover, many existing clustering methods require the user to specify the number of clusters, which is not available in advance. This paper proposes a new class of models for data clustering that addresses set-valued data as well as unknown number of clusters, using a Dirichlet Process mixture of Poisson random finite sets. We also develop an efficient Markov Chain Monte Carlo posterior inference technique that can learn the number of clusters and mixture parameters automatically from the data. Numerical studies are presented to demonstrate the salient features of this new model, in particular its capacity to discover extremely unbalanced clusters in data.