## 4 Performance Demonstrations  
This section reports and discusses several experiments performed to demonstrate the performance of the developed hardware. In particular, to assess the compliance and whole-body motion capability, various tests involving locomotion, stair climbing, exiting a vehicle, etc., were performed. As mentioned in Section 1, compliance reduces physical damage or instability from unexpected contacts. Therefore, compliance helps increase robot stability and balance during contact situations. However, compliance from low-stiffness actuators in the supporting limb often causes problems during humanoid bipedal walking, which degrades the performance and stability. To overcome this problem, in a previous work, we presented the actuator elasticity compensator [16]. To enhance the swing leg compliance and overcome the negative features of the supporting leg, the following studies were conducted. External joint encoders were installed to measure the actuator deformation [23]. A linear quadratic regulator (LQR)-based trajectory tracking controller and disturbance observer (DOB)-based compliance controller, which were presented in our previous work [29], were also employed, along with a walking pattern generator with improved stability proposed by [PERSON] et al. [30]. Using these new algorithms, JET can walk faster and with better stability than THORMANG. To minimize the COM velocity fluctuation, model predictive control-based pattern generation was developed and verified for JET [31]. Whole-body motion capability was verified through the following experiments. Stair climbing and egress experiments were chosen among the DRC Finals missions. Both tasks were the hardest tasks in the DRC Finals because THORMANG has short legs for these missions. First, the lower body workspaces were validated through stair climbing experiments on 23 cm high stairs, which were the same height as the stairs used in the DRC Finals. As shown in Figure 10, JET walked up the stairs without any of the THORMANG strategies applied at the DRC. That is, THORMANG climbed the stairs without bumping into the stairs themselves by grabbing the rails and walking backwards [11]. The required foot workspaces of the JET for climbing stairs are \(\pm\)30 cm for x-axis, \(\pm\)17 cm for y-axis, and 23 cm for z-axis as shown in Figure 10. The x and z axis workspaces are determined by the dimensions of the stairs. Figure 11 shows the total foot workspace of JET, THORMANG, and HRP-5P and the required workspaces of the robots. In Figure 11d, JET has a 32 cm z-axis workspace from \(-\)75 cm to \(-\)43 cm. In the same way, HRP-5P has a 34 cm z-direction workspace from \(-\)77 cm to \(-\)43 cm, but THORMANG has only a 17 cm z-direction workspace from \(-\)59 cm to \(-\)42 cm. In this experiment, JET used the same walking pattern generation algorithm which was used at the DRC Finals [11]. Next, we confirmed the robot could rise from a 64 cm high vehicle seat using whole-body motion with multiple contacts. Figure 12 shows snapshots of the robot egress from the vehicle. In this experiment, the robot performed whole-body motion with contacts at the gripper, pelvis, and two feet. The gripper holds the hand rail to stabilize the body during the JET stand-up. This demonstrated not only the improved robot workspaces, but also the robot's capability to execute compliant motion in multiple-contact situations. In this experiment, the personal mobility vehicle which was designed for adults is used. The height of the vehicle seat is 56 mm, which is shorter than the fully stretched leg length of THORMANG. In Figure 13, JET manipulated objects with the gripper developed by [PERSON] and [PERSON] and teleoperation systems [32].