Human-Robot Integration for Pose Estimation and Semi-Autonomous Navigation on Unstructured Construction Sites

Abstract

Compared to widespread successful deployment of robotic manipulators for repetitive and hazardous tasks in related industries such as manufacturing, the construction industry has achieved relatively limited benefits from robotics and soft automation. Unlike manufacturing, where robotic solutions benefit from the structured layout of the environment (e.g., factory assembly line), construction robots face unique challenges that arise from the rugged, dynamic, and unstructured environment of the work site, as well as the uncertainty and evolving sequence of occurring on-site events. This challenges any intended construction robots to not only replicate basic human motion, but also be capable of sensing and adapting to environmental changes, and making decisions based on the evolving state of the environment. Building upon recent advancements in robotic mapping, computer vision, and object recognition, the authors propose to introduce autonomous behavior at the basic task level for on-site construction robots to address these challenges in a flexible and extensible manner. This paper reports the outcome of the first phase of this research -a structured methodology for improved design and development of basic task automations -and focuses on algorithms developed for mobile robot navigation and relative pose estimation. The algorithms are implemented on a prototype mobile robotic platform, and evaluated in several experimental scenarios.

A Synopsis of 3D Printing and Robotics Applications in Construction

“…Feng et al [12] identified the rugged, dynamic, and unstructured environment of the construction worksite as well as the uncertainty and evolving sequence of on-site events as unique challenges that stand in the way of widespread use of robotics and soft automation in construction. They noted that the challenge for the robotics industry that wants to cater to the construction sector is to design and build robots that are capable of sensing and adapting to environmental changes, in addition to the ability to replicate basic human motion.…”

Infrastructureless approach for ubiquitous user location tracking in construction environments

“…However, in these works, the entities to be tracked were manually marked. Additionally, application of fiducial markers has been suggested by several researchers [24] but the systems are infrastructure-dependent and require the markers to be attached to various surfaces on construction sites. This challenges their applications for large-scale implementations [5].…”

Adaptive Automation for Customized Products

“…As evidenced by the evolution of knowledge representation within these systems, ongoing efforts are directed towards refining information structuring and utilization to enhance automation capabilities throughout the design process. However, unlike controlled environments in manufacturing, where automation flourishes, the dynamics of unstructured environments introduce complexities characterized by unclear task definitions and unknown variables [6]. These unique challenges inherent in unstructured environments significantly impede the efficiency and adaptability of automation systems.…”