Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
An open-access curriculum module exploring the architectural frameworks, communication bounds, and machine learning topologies that govern distributed robotics. Covers three-tier cyber-physical hierarchies (embedded edge devices, local fog/edge servers, centralized hyper-scale cloud), non-minimum phase transfer functions, phase lag in delayed feedback control systems, federated learning parameter aggregation, and binary integer programming formulations for multi-robot task allocation (MRTA). Includes an engineering challenges breakdown—addressing non-deterministic network jitter via Smith predictors, sensor bandwidth bottlenecks via edge feature extraction, Byzantine-tolerant model aggregation, and defense-in-depth cyber-physical security—along with a structured technical glossary, interactive quick reviews, conceptual self-assessments, and 12 fully worked LaTeX numerical engineering solutions.
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
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This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.
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This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
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It is found that roles of MVPs in startups were not fully aware by entrepreneurs, and entrepreneurs should consider a systematic approach to fully explore the value of MVP, as a multiple facet product (MFP).
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It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.
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A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
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A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.
