# Single Leg Gait Tracking of Lower Limb Exoskeleton Based on Adaptive Iterative Learning Control
## 5 Discussion  
The lower limb exoskeletons can be divided into three broad categories based on their functionalities. The first category is human performance augmentation exoskeletons for increasing strength, endurance, and other physical capabilities for able-bodied individuals. This type of exoskeleton can be used for lifting heavy objects, carrying heavy loads over large distances, or working with heavy tools. The likely settings for these devices are in warehouses, construction sites, emergency relief operations, or military bases and excursions. The second broad category encompasses assistive devices for individuals with disabilities. Stroke, spinal cord injury, muscle weakness, and other neurological or musculature disorders can lead to difficulty walking or making arm movements. Current estimates suggest that in the United States alone there are 11.7 million individuals who experience difficulty walking and 8.8 million individuals who experience difficulty lifting objects [24]. Assistive robotic exoskeletons can allow users to complete movements they could not complete on  
\begin{table}
\begin{tabular}{c c c c} \hline \(T_{HR}\)/(N\(im\)) & \(A\) & **Error of Hip Joint (deg)** & **Error of Knee Joint (deg)** \\ \hline \multirow{8}{*}{\(T_{HR}=A\)} & \(A=0\) & 0.20 & 0.22 \\  & \(A=1\) & 0.89 & 0.52 \\  & \(A=5\) & 0.49 & 1.32 \\  & \(A=10\) & 0.60 & 1.81 \\  & \(A=15\) & 0.77 & 2.27 \\ \hline \multirow{8}{*}{\(T_{HR}=Asint\)} & \(A=0\) & 0.20 & 0.22 \\  & \(A=1\) & 0.84 & 0.47 \\  & \(A=5\) & 0.44 & 1.19 \\  & \(A=10\) & 0.63 & 1.76 \\  & \(A=15\) & 0.75 & 2.09 \\ \hline \multirow{8}{*}{\(T_{HR}=Arand(1)\)} & \(A=0\) & 0.20 & 0.22 \\  & \(A=1\) & 0.60 & 0.37 \\ \cline{1-1}  & \(A=5\) & 0.83 & 0.98 \\ \cline{1-1}  & \(A=10\) & 0.78 & 1.51 \\ \cline{1-1}  & \(A=15\) & 0.79 & 1.91 \\ \hline \multirow{8}{*}{\(T_{HR}=Arand(1)\)-\(sin(t)\)} & \(A=0\) & 0.20 & 0.22 \\ \cline{1-1}  & \(A=1\) & 0.57 & 0.33 \\ \cline{1-1}  & \(A=5\) & 0.81 & 0.83 \\ \cline{1-1}  & \(A=10\) & 0.79 & 1.31 \\ \cline{1-1}  & \(A=15\) & 0.76 & 1.68 \\ \hline \end{tabular}
\end{table}
Table 1: The tracking errors with different forms and amplitudes of \(T_{HR}\).  
Figure 10: The impact of \(T_{HR}\) on trajectory tracking of the hip joint (**left**) and the knee (**right**) joint.  
their own. For example, many of these exoskeletons are intended to allow an individual with lower limb paralysis to walk with the aid of crutches. The third broad category is therapeutic exoskeletons for rehabilitation. These devices can assist, resist, or perturb the user's movements to achieve therapeutic exercise. They can train an individual's muscles and/or nervous system to help them overcome the limitations of a disability when they are not using the exoskeleton. With this proposed study, all types of lower limb exoskeletons can benefit. In the practical application, lower limb exoskeletons have to be applied in complex environmental disturbances and more complex and diversified gaits. It is worthwhile to improve its feasibility by reducing tracking errors and adapting to different working environments and human gaits.  
In addition, the proposed method in this study is more suitable for the passive rehabilitation assistance robot as it regards tracking error minimization and safety as a priority. When applied to other purposes, this study is subject to several limitations. First, active lower limb exoskeletons require coordinated movement of both legs. As both legs have complicated interactive movements in non-plane 3D spaces, future work should focus on establishing their trajectory interrelationships. Also, future research should consider the trajectory tracking of the coordinated movement of the legs of the lower limb exoskeleton and optimize trajectory tracking on the basis of different physical environments.