Are Autonomous Mobile Robots Able to Take Over Construction? A Review

Although construction has been known as a highly complex application field for autonomous robotic systems, recent advances in this field offer great hope for using robotic capabilities to develop automated construction. Today, space research agencies seek to build infrastructures without human intervention, and construction companies look to robots with the potential to improve construction quality, efficiency, and safety, not to mention flexibility in architectural design. However, unlike production robots used, for instance, in automotive industries, autonomous robots should be designed with special consideration for challenges such as the complexity of the cluttered and dynamic working space, human-robot interactions and inaccuracy in positioning due to the nature of mobile systems and the lack of affordable and precise self-positioning solutions. This paper briefly reviews state-ofthe-art research into automated construction by autonomous mobile robots. We address and classify the relevant studies in terms of applications, materials, and robotic systems. We also identify ongoing challenges and discuss about future robotic requirements for automated construction

Autonomous Construction of Separated Artifacts by Mobile Robots Using SLAM and Stigmergy

Autonomous mobile robots equipped with arms have the potential to be used for automated construction of structures in various sizes and shapes, such as houses or other infrastructures. Existing construction processes, like many other additive manufacturing processes, are mostly based on precise positioning, which is achieved by machines that have a fixed mechanical link with the construction and therefore relying on absolute positioning. Mobile robots, by nature, do not have a fixed referential point, and their positioning systems are not as accurate as fixed-based systems. Therefore, mobile robots have to employ new technologies and/or methods to implement precise construction processes. In contrast to the majority of prior work on autonomous construction that has relied only on external tracking systems (e.g., GPS) or exclusively on short-range relative localization (e.g., stigmergy), this paper explores localization methods based on a combination of long-range self-positioning and short-range relative localization for robots to construct precise, separated artifacts in particular situations, such as in outer space or in indoor environments, where external support is not an option. Achieving both precision and autonomy in construction tasks requires understanding the environment and physically interacting with it. Consequently, we must evaluate the robot’s key capabilities of navigation and manipulation for performing the construction in order to analyze the impact of these capabilities on a predefined construction. In this paper, we focus on the precision of autonomous construction of separated artifacts. This domain motivates us to combine two methods used for the construction: 1) a self-positioning system and 2) a short-distance relative localization. We evaluate our approach on a miniature mobile robot that autonomously maps an environment using a simultaneous localization and mapping (SLAM) algorithm; the robot’s objective is then to manipulate blocks to build desired artifacts based on a plan given by a human. Our results illuminate practical issues for future applications that also need to integrate complex tasks under mobile robot constraints

Providing and Optimizing a Robotic Construction Plan for Rescue Operations

After a terrible disaster such as an earthquake or a nuclear accident, finding victims and isolating them from hazards are usually the first priorities for rescuers. As the security of rescuers and the stabilization of the environment are critical components of the first rescue phase, we assume that robots could be used to secure the environment by performing construction tasks, to stabilize large structures, and/or protect the victims. In this paper we suggest an approach consisting of using mobile robots to construct protective walls on a site affected by a nuclear disaster. Protective walls can help to block radiation from toxic sources and protect both victims and rescuers. On the other hand, the robot’s vulnerability to radiation restricts its freedom of movements into unsafe regions. Therefore, building protective walls needs a plan (construction plan) that involves three competing objectives: victim safety, rescuer safety, and robot safety. Weighting these factors is a societal choice, is not trivial, and impacts the whole system. In this paper, we provide and optimize the construction plan using a genetic algorithm based on three objectives. We analyze the construction plan performance with respect to execution time. We also analyze the trade-offs involved between these competing objectives in different environments with ranging physical complexity (e.g., a number of victims or sources)