Reconfiguration During Locomotion by Pavement Sweeping Robot With Feedback Control From Vision System

Abstract

Routine cleaning the pavement is an essential requirement to maintain a sustainable environment for social life. The different width and type of pavements raise the challenges for autonomous vehicles with fixed shape to operate effectively. In this paper, we introduce the vision based reconfiguration of self-reconfigurable pavement sweeping robot called Panthera, which can adjust its frame width to ease the cleaning tasks to become friendly with different pavement geometry. The expansion and compression operations of the Panthera width are implemented by rotating one high torque motor connecting with the lead screw rod to change the opening angle of linkage hinges. The Panthera cleaning and locomotion operations are synchronized with changing the robot width according to the output of detected pavement width. To this end, the segmented pavement leveraged on the masked based deep convolutional neural network (DCNN) is used as input for the proposed closed-loop feedback control method, enabling the robot to adjust the requirement of changing the width during locomotion accurately. The proposed PID scheme takes into account the robot kinematic design with the flexibility of width changing modes. The experiments were carried out in real environments demonstrated the autonomous reconfiguration robot width with various locomotion scenarios on pavements of varying width.

Keywords

• Reconfigurable robots
• mechanism design
• feedback control
• sensor fusion
• pavement sweeping robot