Waterproof engineering has deep connection with the safety of buildings. To solve the leakage, we propose a construction robot for waterproofing. Motion control and path planning, the core technologies, are of great significance to promote construction quality. Thus, this paper concentrates on the drive motor control algorithm and navigation strategies under two scenarios.

According to the demand analysis, this thesis first presents the robot’s hardware, the control system based on the STM32F407 mainboard, and a ROS-based navigation system. Simultaneously, the relationship between the drive motors and the robot’s posture is analyzed through the kinematics model.

The core of motion control is to drive the permanent magnet synchronous motor (PMSM) to achieve an accurate response....[ Read more ]

Waterproof engineering has deep connection with the safety of buildings. To solve the leakage, we propose a construction robot for waterproofing. Motion control and path planning, the core technologies, are of great significance to promote construction quality. Thus, this paper concentrates on the drive motor control algorithm and navigation strategies under two scenarios.

According to the demand analysis, this thesis first presents the robot’s hardware, the control system based on the STM32F407 mainboard, and a ROS-based navigation system. Simultaneously, the relationship between the drive motors and the robot’s posture is analyzed through the kinematics model.

The core of motion control is to drive the permanent magnet synchronous motor (PMSM) to achieve an accurate response. This project overcomes the traditional defects, such as poor accuracy and anti-interference, through a self-tuning fuzzy PID controller. Eventually, the simulation and trials verify that this applied optimization strengthens the robustness and precision.

This research demonstrates the promoted A* algorithm based on improved heuristic functions and second-search optimization according to the original drawbacks, which improves its efficiency and quality. Then, the parameters of the evaluation function for the Dynamic Window Approach (DWA) are analyzed. Finally, a fusion algorithm is proposed by utilizing the waypoints derived from the global planner as sub-goals, next applying DWA to obtain the final route. The feasibility is validated through simulation and navigation tests.

As for the construction, the complete coverage strategies based on the linear Charge Coupled Device (CCD) and Ant Colony Optimization (ACO) combined with Boustrophedon Cellular Decomposition (BCD) are developed, respectively. The former identifies the boundary between bitumen-covered flat and unpaved surfaces as the guideline and performs closed-loop control on the robots’ attitude. The latter conducts cellular decomposition via the obstacles’ features and determines the connection sequence of each sub-region and a traversal method to pass over all fields without overlapping.