# Design and Experimental Development of
## 1 Introduction  
A two-legged mobile mechanism that can walk like a human is usually thought as the best suited locomotion method for robots aimed to coexist and collaborate with humans [1]. In the past few decades, bipedal robotic walking has been a hot area in the research of robotics [2; 3; 4; 5]. In order to realize stable walking, the majority of existing biped robots are equipped with rigid flat feet and controlled by a trajectory tracking control method based on the zero moment point (ZMP) theory [6; 7; 8; 9]. The ZMP theory requires that the location on the ground about which the sum of all the moments of the active forces acting on the robot equals zero is strictly within the support polygon of the foot sole [10]. Therefore, the foot that supports the body weight during walking is always kept flat on the ground to obtain the largest support polygon, especially in the single support phase where there is only one foot in contact with the ground [11; 12]. The instantaneous speed of the foot touching the ground is desired to approximate to zero to reduce foot-ground impact. Although effective for walking on flat and structured terrains, this method will cause some problems if the ground is uneven. When a biped robot walks on rough terrain, just a small bump under the sole can significantly reduce the contact area and easily disrupt the walking stability, causing the robot to fall [13]. In addition, if the bump is unforeseen for the control system of the biped robot, the sudden impact with the bump may causesevere shock and vibration to the mechanical system. So several crucial issues involved in walking on rough terrains, such as adaptability on the unevenness, stable foot-ground contact, and shock absorbance still need further investigations. To handle with the above challenges, some researchers focus on the studies of more advanced walking controllers for biped robots. [PERSON] et al. proposed a landing phase control method based on the non-planar contact model of the flexible foot with the environment, and made the biped robot adaptable to the changes of the ground [14]. To achieve dynamic stable walking on rough ground, [PERSON] et al. designed a high-frequency pattern generator which considered the current actual motion of the robot as the initial conditions of each generation [15]. In [16], a graph-based footstep planning approach was proposed to generate the whole step sequences in rough terrain scenarios using a black box walking controller. In [17], the preplanned trajectories were modified online to guarantee a smooth landing after the detection of the foot touching the uneven ground. However, the above controllers depended on some sensors, such as inertial measurement units, contact switches, or laser scanners, to obtain the robot motion state and terrain profile information. The sensor signals must be collected and processed correctly and reliably in real-time, and accurate models of robot kinematics, dynamics, foot-ground contact, and terrain shapes were usually required by the online walking pattern generation and modification. Additionally, as the integrations of on-board sensing, pattern generation, and walking control, the controllers had to perform very large computations at a very high speed [18]. These issues cause many difficulties in the implementations of the controllers. On the other hand, considering that the foot is the only part of the whole biped robot that interacts directly with the environment, it is a feasible approach to improve walking performance on rough terrain through novel foot mechanisms. Some robotic foot systems were designed by adding toe joints and elastic elements to the simple rigid flat foot [19; 20; 21; 22; 23]. Segmented to the heel part and toe part, human-like heel contact and toe contact were realized in bipedal robotic walking [20]. These feet were able to dissipate energy from the heel strike with the elasticity of the heel [21; 22], and to provide more traction using the toe pad at the push-off phase [23], but they could not adapt to rough terrain.