Systematic Literature Review of Mobile Robot Navigation for Construction Environments

Summary

Beschreibung Background Autonomous mobile robots are increasingly deployed in complex, dynamic environments, from indoor warehouses to outdoor construction sites. While semantic navigation approaches have advanced significantly in structured indoor and outdoor environments, their application to construction sites remains limited, where robots must not only navigate terrain but also interpret the functional role of objects and actively coordinate with human workers and machines. For construction applications, this is critical: a mobile robot approaching a material pile for loading, docking with other machines, or negotiating passage with a human worker requires context-aware behavior, not reactive avoidance alone. To characterise this gap, a three-axis classification framework has been developed: (1) Environment (Structured indoor → Unstructured outdoor → Construction site), (2) World Representation (Geometric → Semantic labels → Goal-oriented → Task-aware roles), and (3) Interaction Mode (None → Passive avoidance → Active one-directional → Active bidirectional). An initial survey of seven representative works confirms that no existing study simultaneously reaches the highest level on all three axes. However, this survey is not yet systematic and requires a rigorous, reproducible methodology to substantiate the gap claim. Objective The goal of this thesis is to conduct a PRISMA-compliant systematic literature review (SLR) that rigorously maps the state of the art in mobile robot navigation along the three axes, and provides a quantitative, reproducible basis for the research gap underpinning this dissertation. Your tasks include: Protocol Design: • Define and pre-register the search protocol (search question, inclusion/exclusion criteria, coding scheme) before screening begins. Systematic Search and Screening: • Execute a Boolean keyword search across Scopus, IEEE Xplore, and Web of Science (target: ≥30 included papers). • Apply inclusion/exclusion criteria and document all decisions in a PRISMA 2020 flow diagram. Data Extraction and Coding: • Assign an axis-level score to each paper on all three axes using operationalised decision rules. Analysis and Visualisation: • Produce an extended comparison matrix (≥30 papers) and three gap heat-maps visualising empty axis-combination cells. • Write a narrative synthesis per sub-domain (construction automation, outdoor navigation, social/indoor HRI, human-aware planning). Voraussetzungen Profile • Studies in Mechanical Engineering, Informatics, or a related field. • Interest in robotics, autonomous systems, and scientific literature methodology. • Ability to work independently and in a structured, systematic way. • Good English skill. Start Immediately / by arrangement If you are interested, please send your application including your CV and academic transcript via email.

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