Abstract:Recent advancements in robotics empower the exploration of remote construction methods aimed at reducing the risk for workers. As the global pandemic places construction workers and their communities at high risk for disease, the need for remote construction methods increases. Such methods depend on the complicated task of controlling mobile robotic platforms in real-time. In this context, this paper presents workin-progress in development and experimentation with a tool for collaborative earthworks using mult… Show more
“…8-9). The planner is aimed at assisting the production of motion instructions for a ROS-controlled vehicle by complementing two previous publications on controlling the UGV and lo-calizing it using an unmanned aerial vehicle (UAV) [6], [7]. As the planner generates a path for the aggregate-forming task, future work will focus on integrating this capability for large-scale experiments involving outdoor construction site preparation tasks.…”
Section: Discussionmentioning
confidence: 99%
“…This research is pursued in the context of autonomous earthworks [1], environmental purposes [2], military applications [3], landscape architecture [4], and construction [5]. Existing research includes the development of dedicated tools for automating earthworks [6], methods, and protocols supporting such processes [7]- [9].…”
Research in advanced construction and autonomous earthworks begins to explore the shaping of aggregates for construction, military, and environmental purposes. However, there is currently no existing work on moving aggregates to form specific shapes on a surface. This action can aid in gathering aggregates for on-site construction of re-configurable formations, performing architectural tasks, or piling material reservoirs for concrete production. To support aggregate-forming, an autonomous agent is required to move non-labeled aggregates from multiple locations to numerous proximate target points in a predefined desired shape. In this process, the agent needs to push the aggregates, handle material spills, and update both the material location and the outcome formation. The paper presents a planner for autonomous aggregate shaping to support this task. The path generation is first demonstrated in a simulation environment and then validated in an in-lab experimental setup. The results show that employing the planner can assist in advancing the manipulation of aggregates beyond pushing and grading and toward the on-site shaping of aggregates into desired forms.INDEX TERMS Advanced construction, autonomous earthworks, path planning, robotics and automation.
“…8-9). The planner is aimed at assisting the production of motion instructions for a ROS-controlled vehicle by complementing two previous publications on controlling the UGV and lo-calizing it using an unmanned aerial vehicle (UAV) [6], [7]. As the planner generates a path for the aggregate-forming task, future work will focus on integrating this capability for large-scale experiments involving outdoor construction site preparation tasks.…”
Section: Discussionmentioning
confidence: 99%
“…This research is pursued in the context of autonomous earthworks [1], environmental purposes [2], military applications [3], landscape architecture [4], and construction [5]. Existing research includes the development of dedicated tools for automating earthworks [6], methods, and protocols supporting such processes [7]- [9].…”
Research in advanced construction and autonomous earthworks begins to explore the shaping of aggregates for construction, military, and environmental purposes. However, there is currently no existing work on moving aggregates to form specific shapes on a surface. This action can aid in gathering aggregates for on-site construction of re-configurable formations, performing architectural tasks, or piling material reservoirs for concrete production. To support aggregate-forming, an autonomous agent is required to move non-labeled aggregates from multiple locations to numerous proximate target points in a predefined desired shape. In this process, the agent needs to push the aggregates, handle material spills, and update both the material location and the outcome formation. The paper presents a planner for autonomous aggregate shaping to support this task. The path generation is first demonstrated in a simulation environment and then validated in an in-lab experimental setup. The results show that employing the planner can assist in advancing the manipulation of aggregates beyond pushing and grading and toward the on-site shaping of aggregates into desired forms.INDEX TERMS Advanced construction, autonomous earthworks, path planning, robotics and automation.
Construction site preparation tasks rely on experienced operators and heavy machinery for clearing debris, earthmoving, leveling, and soil stabilization. These actions require complex collaboration between human teams to survey the site, estimate the material condition, and guide the operators accordingly. In recent years there has been a critical labor shortage due to increasing demands in construction. Integrating autonomous systems can mitigate this gap by replacing traditional methods with robotic solutions. However, while ideal conditions for automatic systems are static and highly controlled, construction sites are dynamic and unstructured environments. The ability of autonomous systems to overcome these conditions during outdoor construction site preparation tasks relies on their capacity to map the material on-site and continuously perform localization. This study suggests a solution to these problems by collaborating between an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV). In this method, the UAV produces a material map and monitors the UGV's location relative to known static landmarks. These measurements are then sent to the ground vehicle and are added to the onboard sensors using the Extended Kalman Filter (EKF) approach. Thus, the UAV enhances the operation of the UGV by providing an accurate localization and mapping from the air and allowing it to perform a site-preparation task beyond mere sensing. This approach is examined with simulation and validated by outdoor experiments. Additionally, this method is integrated within Shepherd, a custom-developed plugin for computer-aided design applications.
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