## 5 Conclusions  
In this paper, we proposed a robotic framework consisting of recognition modules and a state machine control module to address the recovery problem that occurs when the target person being followed is lost. We designed a novel method for a robot to recover to the tracking state when a target person disappears by predicting the target's future path based on the past trajectory and planning the movement path accordingly. Although the proposed approach is promising for trajectory prediction and recovery of the missed target, it has some limitations. We elaborate on the issues and future works in the following. First, the trajectory prediction was based only on estimating the direction of the future movement of the target. It is necessary to further develop the trajectory prediction to allow for complicated trajectories that are more naturally in map geometries so that the prediction can still work in more complicated environments, e.g., U-turns. Second, because of the limitations in the robot's capabilities such as its sensor range and speed for stability, the persons needed walk slower than the normal walking speed and even wait for the robot to recover. These issues could be improved significantly if we use a robot system with higher performance sensors and a mobile base and optimize  
\begin{table} \begin{tabular}{l l c c c c c c c c c c c c} \hline \hline  & **Performance Measures** & **Exp.1** & **Exp.2** & **Exp.3** & **Exp.4** & **Exp.5** & **Exp.6** & **Exp.7** & **Exp.8** & **Exp.9** & **Exp.10** & **Total** & **Average** & **Std** \\ \hline \multirow{10}{*}{**Overall**} & Experiment status & O & O & O & O & O & O & O & O & O & O & - & - \\  & Target’s travel distance (m) & 28.3 & 28.3 & 28.5 & 28.9 & 29.5 & 29.3 & 27.9 & 29.4 & 29.3 & 29.4 & 288.9 & 28.9 & 0.57 \\  & Robot’s travel distance (m) & 26.4 & 27.2 & 27.8 & 26.9 & 27.2 & 27.4 & 27.0 & 27.4 & 27.8 & 27.9 & 273.0 & 27.3 & 0.47 \\  & Robot’s travel time (s) & 46.2 & 52.5 & 46.0 & 46.6 & 47.8 & 48.3 & 46.8 & 46.1 & 50.5 & 48.0 & 478.8 & 47.9 & 2.12 \\  & Robot’s average velocity (m/s) & 0.57 & 0.52 & 0.60 & 0.58 & 0.57 & 0.57 & 0.58 & 0.60 & 0.55 & 0.58 & - & 0.57 & 0.02 \\  & No. of frames & 1148 & 1281 & 1103 & 1151 & 1185 & 1154 & 1158 & 1128 & 1231 & 1188 & 11727 & 1173 & 52 \\  & Successful tracking (frames) & 978 & 1085 & 964 & 1000 & 960 & 921 & 1001 & 909 & 1066 & 1011 & 9895 & 990 & 56 \\  & Lost tracking (frames) & 170 & 196 & 139 & 151 & 225 & 233 & 157 & 219 & 165 & 177 & 1832 & 183 & 33.16 \\  & Successful tracking (s) & 39.4 & 44.4 & 40.2 & 40.5 & 38.7 & 38.5 & 40.5 & 37.1 & 43.8 & 40.8 & 40.0 & 40.4 & 2.26 \\  & Lost tracked (s) & 6.8 & 8.0 & 5.8 & 6.1 & 9.1 & 9.7 & 6.3 & 8.9 & 6.8 & 7.1 & 74.8 & 7.5 & 1.38 \\  & Lost tracking rate (\%) & 0.15 & 0.15 & 0.13 & 0.13 & 0.19 & 0.20 & 0.14 & 0.19 & 0.13 & 0.15 & - & 0.16 & 0.03 \\  & Successful tracking rate (\%) & 0.85 & 0.85 & 0.87 & 0.87 & 0.81 & 0.80 & 0.86 & 0.81 & 0.87 & 0.85 & - & 0.84 & 0.03 \\  & FFS & 24.8 & 24.4 & 24.0 & 24.7 & 24.8 & 23.9 & 24.7 & 24.5 & 24.4 & 24.8 & - & 24.49 & 0.34 \\ \hline \multirow{10}{*}{**Comer**} & Trajectory prediction status & O & O & O & O & O & O & O & O & O & O & - & - & - \\  & Time when losing (s) & 20.1 & 17.7 & 20.5 & 18.1 & 20.0 & 22.0 & 15.5 & 17.8 & 21.5 & 17.6 & - & 19.07 & 2.04 \\  & Time when recovering (s) & 25.0 & 22.0 & 24.5 & 22.5 & 22.0 & 25.9 & 19.6 & 22.8 & 26.2 & 21.5 & - & 23.20 & 2.14 \\ \cline{1-1}  & Recovery time (s) & 5.0 & 4.3 & 4.0 & 4.4 & 1.9 & 4.0 & 4.0 & 5.1 & 4.7 & 3.9 & - & **4.13** & 0.88 \\ \cline{1-1}  & TDR when losing (m) & 5.1 & 5.5 & 5.2 & 5.5 & 5.8 & 5.9 & 5.1 & 6.0 & 6.1 & 5.6 & - & 5.59 & 0.36 \\ \cline{1-1}  & TDR when recovering (m) & 7.2 & 7.3 & 7.0 & 6.8 & 6.1 & 7.7 & 7.0 & 7.7 & 7.6 & 7.4 & - & 7.18 & 0.48 \\ \cline{1-1}  & Recovery distance (m) & 2.1 & 1.8 & 1.8 & 1.4 & 0.3 & 1.8 & 1.9 & 1.7 & 1.5 & 1.8 & - & **1.60** & 0.49 \\ \cline{1-1}  & Recovery velocity (m/s) & 0.42 & 0.41 & 0.45 & 0.32 & 0.16 & 0.45 & 0.46 & 0.34 & 0.31 & 0.46 & - & **0.38** & 0.10 \\ \hline \hline \end{tabular}