The impact of RFID technology on warehouse process innovation: A pilot project in the TPL industry

Using the value chain model which provides a process view, this longitudinal case study and simulation modeling analysis of a Canadian third-party logistics (TPL) supply chain provides some empirical support for the enabling role of RFID technology in effecting warehouse process innovation and optimization for the focal TPL firm. However, the findings of our study also reveal the RFID technology implementation costs as the key inhibitor of RFID widespread adoption and usage among suppliers. This, in turn, precluded the focal TPL firm from implementing the best optimum RFID solution to create better business value from the RFID project.     

RANGE–Robust autonomous navigation in GPS‐denied environments

This paper addresses the problem of autonomous navigation of a micro air vehicle (MAV) in GPS‐denied environments. We present experimental validation and analysis for our system that enables a quadrotor helicopter, equipped with a laser range finder sensor, to autonomously explore and map unstructured and unknown environments. The key challenge for enabling GPS‐denied flight of a MAV is that the system must be able to estimate its position and velocity by sensing unknown environmental structure with sufficient accuracy and low enough latency to stably control the vehicle. Our solution overcomes this challenge in the face of MAV payload limitations imposed on sensing, computational, and communication resources. We first analyze the requirements to achieve fully autonomous quadrotor helicopter flight in GPS‐denied areas, highlighting the differences between ground and air robots that make it difficult to use algorithms developed for ground robots. We report on experiments that validate our solutions to key challenges, namely a multilevel sensing and control hierarchy that incorporates a high‐speed laser scan‐matching algorithm, data fusion filter, high‐level simultaneous localization and mapping, and a goal‐directed exploration module. These experiments illustrate the quadrotor helicopter's ability to accurately and autonomously navigate in a number of large‐scale unknown environments, both indoors and in the urban canyon. The system was further validated in the field by our winning entry in the 2009 International Aerial Robotics Competition, which required the quadrotor to autonomously enter a hazardous unknown environment through a window, explore the indoor structure without GPS, and search for a visual target. © 2011 Wiley Periodicals, Inc.     

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale to the generative and non-parametric clustering setting by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the sources. The commonalities between the sources are modeled by an infinite component model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. We discover complex relationships between the marginals (that are multimodal in both marginals) that would remain undetected by simpler models. Cluster analysis of co-expression is a standard method of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation.     

Setpoint regulation for stochastically interacting robots

We present an integral feedback controller that regulates the average copy number of an assembly in a system of stochastically interacting robots. The mathematical model for these robots is a tunable reaction network, which makes this approach applicable to a large class of other systems, including ones that exhibit stochastic self-assembly at various length scales. We prove that this controller works for a range of setpoints and how to compute this range both analytically and experimentally. Finally, we demonstrate these ideas on a physical testbed.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.     

An Optimizing Compiler for Parallel Chemistry Simulations

Well designed domain specific languages have three important benefits: (1) the easy expression of problems, (2) the application of domain specific optimizations (including parallelization), and (3) dramatic improvements in productivity for their users. In this paper we describe a compiler and parallel runtime system for modeling the complex kinetics of rubber vulcanization and olefin polymerization that achieves all of these goals. The compiler allows the development of a system of ordinary differential equations describing a complex vulcanization reaction or single-site olefin polymerization reaction—a task that used to require months—to be done in hours. A specialized common sub-expression elimination and other algebraic optimizations sufficiently simplify the complex machine generated code to allow it to be compiled—eliminating all but 8.0% of the operations in our largest program and enabling over 60 times faster execution on our largest benchmark codes. The parallel runtime and dynamic load balancing scheme enables fast simulations of the model.     

Naturalistic study of the risky situations faced by novice riders

This article sets out to identify the typical risky situations experienced by novice motorcyclists in the real world just after licensing. The procedure consists of a follow-up of six novices during their first two months of riding with their own motorbike instrumented with cameras. The novices completed logbooks on a daily basis in order to identify the risky situations they encountered, and were given face-to-face interviews to identify the context and their shortcomings during the reported events. Data show a large number of road configurations considered as risky by the riders (248 occurrences), especially during the first two weeks. The results revealed that a lack of hazard perception skills contributed to the majority of these incidents. These situations were grouped together to form clusters of typical incident scenarios on the basis of their similarities. The most frequent scenario corresponds to a lane change in dense traffic (15% of all incidents). The discussion shows how this has enhanced our understanding of novice riders’ behaviour and how the findings can improve training and licensing. Lastly, the main methodological limitations of the study and some guidelines for improving future naturalistic riding studies are presented.

Practitioner Summary:

This article aims to identify the risky situations of novice motorcyclists in real roads. Two hundred forty-eight events were recorded and 13 incident scenarios identified. Results revealed that a lack of hazard perception contributed to the majority of these events. The most frequent scenario corresponds to a lane change in dense traffic.     

A method for a robust optimization of joint product and supply chain design

This paper proposes a method for finding a robust solution to the problem of joint product family and supply chain design. Optimizing product design and the supply chain network at the same time brings substantial benefits. However, this approach involves decisions that can generate uncertainties in the long term. The challenge is to come up with a method that can adapt to most possible environments without straying too far from the optimal solution. Our approach is based on the generation of scenarios that correspond to combinations of uncertain parameters within the model. The performance of designs resulting from these scenario optimizations are compared to the performance of each of the other design scenarios, based on their probability of occurrence. The proposed methodology will allow practitioners to choose a suitable design, from the most profitable to the most reliable.