Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Design and Simulation of Time-energy Optimal Anti-swing Trajectory Planner for Autonomous Tower Cranes

Souravik Dutta, Yiyu Cai

TL;DR

This work presents an offline, time-energy optimal anti-swing trajectory planner for autonomous tower cranes by leveraging differential flatness of the trolley-payload and jib-payload subsystems and Bézier-parameterized flat outputs. It formulates constrained multi-objective optimization problems for hoist, trolley, and slew motions and solves them with two MOEAs, NSGA-II and GDE3, selecting GDE3 for its superior solution spread and convergence; a fuzzy Membership-based selection yields a single operational plan. The planner integrates with the CALP system to produce collision-free, residual-swing-free reference trajectories that respect actuation and safety limits, demonstrated via MATLAB/PlatEMO simulations on a 1:10 crane model. The results show successful elimination of residual swing and adherence to boundary constraints, highlighting the method’s potential for real-time or near-real-time trajectory planning in autonomous construction settings, while acknowledging the need for a feedback controller to handle disturbances. Future work will focus on robust tracking to compensate for disturbances and model uncertainties during actual operation.

Abstract

For autonomous crane lifting, optimal trajectories of the crane are required as reference inputs to the crane controller to facilitate feedforward control. Reducing the unactuated payload motion is a crucial issue for under-actuated tower cranes with spherical pendulum dynamics. The planned trajectory should be optimal in terms of both operating time and energy consumption, to facilitate optimum output spending optimum effort. This article proposes an anti-swing tower crane trajectory planner that can provide time-energy optimal solutions for the Computer-Aided Lift Planning (CALP) system developed at Nanyang Technological University, which facilitates collision-free lifting path planning of robotized tower cranes in autonomous construction sites. The current work introduces a trajectory planning module to the system that utilizes the geometric outputs from the path planning module and optimally scales them with time information. Firstly, analyzing the non-linear dynamics of the crane operations, the tower crane is established as differentially flat. Subsequently, the multi-objective trajectory optimization problems for all the crane operations are formulated in the flat output space through consideration of the mechanical and safety constraints. Two multi-objective evolutionary algorithms, namely Non-dominated Sorting Genetic Algorithm (NSGA-II) and Generalized Differential Evolution 3 (GDE3), are extensively compared via statistical measures based on the closeness of solutions to the Pareto front, distribution of solutions in the solution space and the runtime, to select the optimization engine of the planner. Finally, the crane operation trajectories are obtained via the corresponding planned flat output trajectories. Studies simulating real-world lifting scenarios are conducted to verify the effectiveness and reliability of the proposed module of the lift planning system.

Design and Simulation of Time-energy Optimal Anti-swing Trajectory Planner for Autonomous Tower Cranes

TL;DR

This work presents an offline, time-energy optimal anti-swing trajectory planner for autonomous tower cranes by leveraging differential flatness of the trolley-payload and jib-payload subsystems and Bézier-parameterized flat outputs. It formulates constrained multi-objective optimization problems for hoist, trolley, and slew motions and solves them with two MOEAs, NSGA-II and GDE3, selecting GDE3 for its superior solution spread and convergence; a fuzzy Membership-based selection yields a single operational plan. The planner integrates with the CALP system to produce collision-free, residual-swing-free reference trajectories that respect actuation and safety limits, demonstrated via MATLAB/PlatEMO simulations on a 1:10 crane model. The results show successful elimination of residual swing and adherence to boundary constraints, highlighting the method’s potential for real-time or near-real-time trajectory planning in autonomous construction settings, while acknowledging the need for a feedback controller to handle disturbances. Future work will focus on robust tracking to compensate for disturbances and model uncertainties during actual operation.

Abstract

For autonomous crane lifting, optimal trajectories of the crane are required as reference inputs to the crane controller to facilitate feedforward control. Reducing the unactuated payload motion is a crucial issue for under-actuated tower cranes with spherical pendulum dynamics. The planned trajectory should be optimal in terms of both operating time and energy consumption, to facilitate optimum output spending optimum effort. This article proposes an anti-swing tower crane trajectory planner that can provide time-energy optimal solutions for the Computer-Aided Lift Planning (CALP) system developed at Nanyang Technological University, which facilitates collision-free lifting path planning of robotized tower cranes in autonomous construction sites. The current work introduces a trajectory planning module to the system that utilizes the geometric outputs from the path planning module and optimally scales them with time information. Firstly, analyzing the non-linear dynamics of the crane operations, the tower crane is established as differentially flat. Subsequently, the multi-objective trajectory optimization problems for all the crane operations are formulated in the flat output space through consideration of the mechanical and safety constraints. Two multi-objective evolutionary algorithms, namely Non-dominated Sorting Genetic Algorithm (NSGA-II) and Generalized Differential Evolution 3 (GDE3), are extensively compared via statistical measures based on the closeness of solutions to the Pareto front, distribution of solutions in the solution space and the runtime, to select the optimization engine of the planner. Finally, the crane operation trajectories are obtained via the corresponding planned flat output trajectories. Studies simulating real-world lifting scenarios are conducted to verify the effectiveness and reliability of the proposed module of the lift planning system.
Paper Structure (32 sections, 87 equations, 13 figures, 9 tables, 2 algorithms)

This paper contains 32 sections, 87 equations, 13 figures, 9 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background and Motivation
  3. Literature Review
  4. Limitations of Existing Research
  5. Contributions of the Proposed Method
  6. Robotized Model of the Tower Crane
  7. Kinematic Model
  8. Dynamic Model
  9. Trolley operation dynamics
  10. Slew operation dynamics
  11. Multi-objective Trajectory Optimization Problem
  12. Hoist Trajectory Optimization Problem
  13. Hoist trajectory parameterization
  14. Trolley Trajectory Optimization Problem
  15. Differential flatness of trolley-payload system
  16. ...and 17 more sections

Figures (13)

  • Figure 1: Structure of the robotized tower crane with actuated and unactuated DOFs.
  • Figure 2: Auxiliary DOF for the trolley-payload system during trolley operation.
  • Figure 3: Auxiliary DOFs for the jib-payload system during slew operation.
  • Figure 4: Position of the trolley and the payload during slew operation.
  • Figure 5: Anti-swing tower crane trajectory planning architecture for the CALP system.
  • ...and 8 more figures