35,899 research outputs found
Modeling of Complex Parts for Industrial WaterJet Cleaning
Industrial high-pressure waterjet cleaning is common to many industries. The modeling in this paper functions inside a collaborative robotic framework for high mix, low volume processes where human robot collaboration is beneficial. Automation of pressure washing is desirable for economic and ergonomic reasons. An automated cleaning system needs path simulation and analysis to give the operator insight into the predicted cleaning performance of the system. In this paper, ablation, the removal of a substrate coating by waterjet, is modeled for robotic cleaning operations. The model is designed to work with complex parts often found in spray cleaning operations, namely parts containing hidden portions, holes, or concavities. Experimentation is used to validate and calibrate the ablation model to yield accurate evaluations for how well every feature of a part is cleaned based on the cumulative effect of water affecting the part surface. The ablation model will provide the foundation for optimizing process parameters for robotic waterjet cleaning
CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a Multilayer Transportation Network
Mobile phone data have recently become an attractive source of information
about mobility behavior. Since cell phone data can be captured in a passive way
for a large user population, they can be harnessed to collect well-sampled
mobility information. In this paper, we propose CT-Mapper, an unsupervised
algorithm that enables the mapping of mobile phone traces over a multimodal
transport network. One of the main strengths of CT-Mapper is its capability to
map noisy sparse cellular multimodal trajectories over a multilayer
transportation network where the layers have different physical properties and
not only to map trajectories associated with a single layer. Such a network is
modeled by a large multilayer graph in which the nodes correspond to
metro/train stations or road intersections and edges correspond to connections
between them. The mapping problem is modeled by an unsupervised HMM where the
observations correspond to sparse user mobile trajectories and the hidden
states to the multilayer graph nodes. The HMM is unsupervised as the transition
and emission probabilities are inferred using respectively the physical
transportation properties and the information on the spatial coverage of
antenna base stations. To evaluate CT-Mapper we collected cellular traces with
their corresponding GPS trajectories for a group of volunteer users in Paris
and vicinity (France). We show that CT-Mapper is able to accurately retrieve
the real cell phone user paths despite the sparsity of the observed trace
trajectories. Furthermore our transition probability model is up to 20% more
accurate than other naive models.Comment: Under revision in Computer Communication Journa
Time-optimal Coordination of Mobile Robots along Specified Paths
In this paper, we address the problem of time-optimal coordination of mobile
robots under kinodynamic constraints along specified paths. We propose a novel
approach based on time discretization that leads to a mixed-integer linear
programming (MILP) formulation. This problem can be solved using
general-purpose MILP solvers in a reasonable time, resulting in a
resolution-optimal solution. Moreover, unlike previous work found in the
literature, our formulation allows an exact linear modeling (up to the
discretization resolution) of second-order dynamic constraints. Extensive
simulations are performed to demonstrate the effectiveness of our approach.Comment: Published in 2016 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS
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