# Adaptive Navigation in Collaborative Robots: A Reinforcement Learning and Sensor Fusion Approach
## 5 Experimental Results  
To test the navigation and obstacle avoidance capabilities of the test vehicle, a hallway was selected with obstacles arranged in such a way that most are on the right side, while some are positioned at the center and left. Figure 7 below shows the map view of the experiment test path. The purpose of this arrangement is to evaluate the performance of the vehicle's navigation and obstacle avoidance systems, specifically how well the vehicle adapts to varying path conditions. A logging system was installed in the vehicle to record data related to decision-making during navigation, including the vehicle's heading angle and how it adapts to its path. These data were transmitted to a computer via Bluetooth for analysis, and visualization and was used to assess the vehicle's performance. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature** & **Description** & **Cost (INR)** \\ \hline GPS module & High-precision GPS module & 2335–20,000 \\ Magnetometer & High-grade digital compass & 1000 and above \\ Obstacle detection & LiDAR sensor & 5000–10,499 \\ Microcontroller & Many options are available & 8000 and above \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Cost of components used in alternate solutions. \begin{table}
\begin{tabular}{c c} \hline \hline
**Feature** & **Description** \\ \hline Description & The TB6612 FNG is a dual DC motor driver IC by Toshiba \\ Control Capability & Independently controls two DC motors or one bipolar \\ stepper motor & \\ Control Modes & CW (clockwise), CCW (counterclockwise), short-brake, \\ and stop & \\ Voltage Range & 4.5 V to 13.5 V \\ Current Output & 1 A continuous, 3 A peak per channel \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Technical specification of the TB6612 FNG motor driver. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature** & **Description** & **Cost (INR)** \\ \hline GPS module & Ublux Neo 6M & 198 \\ Magnetometer & LIS2 MDL 3-axis & 257 \\ Obstacle detection & HC-SR04 & 55 \\ Microcontroller & ATmega2560 & 2000–4000 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Cost of components used in this study. Using the sequence of decisions made by the vehicle while driving autonomously from the start point to the endpoint, a plot has been created that visually represents the path followed and the decisions made along the way. The x and y axes do not have any specific units; the plot is intended to give a general sense of the vehicle's trajectory and the sequence of decisions taken. This plot facilitates basic path mapping. Figure 8 below illustrates this plot. According to the obstacle avoidance algorithm, the vehicle moves backward when the front sensor detects an obstacle. The black points in Figure 8 indicate backward movement and the presence of obstacles. There are a total of seven clusters of such points on the graph. Nearby black points suggest the vehicle is dealing with the same obstacle, representing a single obstacle. Comparing this path with the test track shown in Figure 7, it closely aligns with the decisions made during the test. Using the data logged from the magnetometer, visualization of the current heading angle of the vehicle can be performed. Figure 9 represents the magnetometer data in polar plot form. Figure 8: Path mapping from test vehicle’s decisions. Figure 7: Test track satellite view. A bar graph representation of the same data is shown below in the same sequence as per vehicle's movement. In both plots, the red color indicates the desired heading to reach the endpoint, while the blue color represents the current heading of the vehicle. Figure 10 shows spikes in the current heading values, which represent either the presence of obstacles and the vehicle's attempts to navigate around them or potential external magnetic disturbances affecting the sensor. A total of seven spike clusters can be observed, which also correspond to the path mapped in Figure 8 using navigation instruction data.