## 6 Experimental Results and Discussion  
The results of forming the global path and shape plan of the proposed method are shown in Figure 16. The positions corresponding to boundary waypoints and narrow spaces are correctly defined. The planned trajectory is marked as yellow color; the narrow space areas are marked as red arrows. The green track in Figure 16 is the path that records the actual locations of the hTetro during the navigation to cover a map, given the path and shape planning. During the real-time implementation, the robot will follow the generated waypoints including both path and shape plans. Shape plan indicates the specific robot morphology at locations derived from the corresponding path plan. When the shape plan of the next waypoint indicates the change from one morphology to other, robot will perform the complete transformation to required morphology before navigating to next waypoint in path plan. It can be seen that hTetro with an onboard rpLidiar laser sensor and reconfiguration abilities can keep track and follow the global plan sufficiently with mirror errors. The Figure 17 provides visual views on how the robot follows the plan set by the global planner to cover the free space areas. From the Figure 17a-d, the free spaces including the narrow space areas are gradually covered by hTetro. The transformation steps of hTetro from O shape to horizontal I shape and from O shape to vertical I shape during autonomous navigation are provided on RVIZ a graphical monitoring tool of ROS in Figures 18 and 19, respectively. The real pictures of hTetro reconfiguration steps to adapt with narrow spaces in the real environment can be observed in Figure 20. As per the results, the robot responds appropriately to morphology and path plan has been designed to cover almost all areas of narrow space. On the other hand, the robot cannot cover these spaces if it does not change its shape to suitable morphology. Figure 16: Global path planner and robot pose during navigation. Figure 17: Areas coverage by the proposed method. (**a**) global path planning, (**b**) reconfiguration form O shape to horizontal I shape to cover narrow spaces, (**c**) reconfiguration form O shape to vertical I shape to cover narrow spaces, (**d**) total covered areas. Figure 18: Morphology reconfigurations from O shape to horizontal I shape to navigate through the narrow spaces constraints on RVIZ. (**a**) Detected narrow spaces as red arrows, (**b**) the position before reconfiguring morphology, (**c**) starting morphology reconfiguration, (**d**) navigating with horizontal I shape, (**e**) Morphology reshapes to O after going out of narrow space, (**f**) keep navigating with O shape. The area coverage results of the proposed method for different map setups are presented in Figure 21. The results show the adaptive ability of the global planner with the diversity of settings from the small map with simple obstacle Figure 21a to moderate obstacle Figure 21b and  
Figure 19: Morphology reconfigurations from O shape to vertical I shape to navigate through the narrow spaces constraints on RVIZ. (**a**) Detected narrow spaces as red arrows, (**b**) the position before reconfiguring morphology, (**c**) starting morphology reconfiguration, (**d**) navigating with vertical I shape, (**e**) Morphology reshapes to O after going out of narrow space, (**f**) keep navigating with O shape. Figure 20: Morphology reconfigurations from O shape to vertical I shape to navigate through the narrow spaces constraints on real environment. (**a**) Detected narrow spaces as red arrows, (**b**) the position before reconfiguring morphology, (**c**) starting morphology reconfiguration, (**d**) navigating with vertical I shape, (**e**) Morphology reshapes to O after going out of narrow space, (**f**) keep navigating with O shape. complicated obstacle Figure 21c. Based on the generated plan, the hTetro can cover the free space areas almost completely.