4.7 Article

Heavy mobile crane lift path planning in congested modular industrial plants using a robotics approach

Journal

AUTOMATION IN CONSTRUCTION
Volume 122, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j..autcon.2020.103508

Keywords

Modular construction; Mobile crane; Path planning; Lift planning; Robotics in construction; Construction automation; Industrial plant

Funding

  1. PCL Industrial Management Inc.
  2. TECNOSA R&D Center at the University of Tehran

Ask authors/readers for more resources

This research proposes an automated lift path planning method for heavy crawler cranes, treating the lifted object as a three-degree-of-freedom convex mobile robot with discretized rotational and continuous translational motions. By simplifying lift path planning into a graph search problem, the shortest path for planar motion of the heavy-lift and its optimal pick-point can be identified.
Lift path planning is a significant subtask in constructability analysis, sequencing, and scheduling of congested industrial modular projects, impacting project cost, and safety. Although intuitive lift planning is still prevalent among the practitioners, this manual process might be tedious and error-prone for hundreds of lifts. This research presents an automated lift path planning method for heavy crawler cranes in no-walk scenarios employing a robotics approach. This method treats the lifted object as a three-degree-of-freedom convex mobile robot with discretized rotational and continuous translational motions. The proposed resolution-complete method models the crane capacity chart, tail-swing, and boom clearances as pseudo-obstacles in the lifted object's configuration space. By reducing the lift path planning to a graph search prblem, if any, the shortest path for the planar motion of the heavy-lift, along with its optimal pick-point, is identified. The developed heavy-lift path planning method is validated via two practical case studies.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available