# Gait Planning Research for an Electrically Driven Large-Load-Ratio Six-Legged Robot
## 1 Introduction  
In nature, the legged animal uses the coordinated motion of their legs to actualize from the current location to the goal location, which is called gait. Generally speaking, the types of gait will increase with the augmentation of legs. Then, the gait planning of legged robots will be more complex. Although the legged robot can have many types of gaits in theory, not every gait can make the robot stably and effectively walk. It is therefore necessary to carry out the analysis of the gait and motion planning. The different mobile system structures of legged robots often need different gait planning strategies. The gait planning of legged robots not only directly affects the consistency and stability, but also relates to the degree of energy dissipation. Many researchers hope to obtain an excellent legged robot which can independently think and work like the animal. Presently, the walking of excellent multi-legged robots mainly depends on the sensing system, control strategy, initial gait planning, etc. The information from the legged robot and environment can be obtained by the sensing system. The initial gait planning is employed andrepaired through the control strategy of the robot. Then, the walking of legged robots can be realized in structured and unstructured environments. The large-load-ratio multi-legged robot can not only carry a variety of detection equipment to carry out the scientific exploration tasks, but can also play the role of the transporter. Hence, the terrain adaptability is needed for large-load-ratio multi-legged robots. To enhance the walking stability of the robot and reduce the impact force of the swing leg to the ground, the large-load-ratio multi-legged robot often requires the installation of an elastic cushion or rubber tire on the end of the foot. The spring and other elastic elements are often installed in the lower limb of the leg by comparing with the non-bearing small multi-legged robot. Hence, the buffer devices can be often found in many large-load-ratio multi-legged robots, such as Big Dog [1; 2], COMET-IV [3; 4], ATHLETE [5; 6], and so on. The gait planning of multi-legged robots is studied by many researchers. [PERSON] [7] used the free gait generation algorithm to make a six-legged robot generate stable gaits based on the commanded velocity. The reinforcement learning was applied to the six-legged robot in real time. [PERSON] [8] modified the conventional wave gaits. The modified versions of the wave gaits are more efficient than the conventional wave gaits. [PERSON] et al. [9] used a simplified neural network model called the associatron to deal with the gait motion planning problem on an irregular field for a six-legged robot. The viability of the proposed method was verified by the simulation and the experiments of the developed robot. [PERSON] et al. [10] presented the crab-type turning gaits for hexapod robots on uneven ground and forbidden zones. The turning gaits were tested by the SILO-6 walking robot. [PERSON] et al. [11] proposed an end-to-end planning method that can achieve the teleoperated mobility of robot in complex environments. [PERSON] and [PERSON] [12] extended the range of forward walking gaits of robots by adjusting the restrictedness controller. The range of wave gaits was then developed. The test experiment was carried out by a small hexapod \"Hamlet\". [PERSON] and [PERSON] [13; 14] addressed the design and operation of hexapod walking robots. The example of gait planning was provided through kinematic and dynamic features of Cassino hexapod leg operation. [PERSON] et al. [15] developed a motion planning algorithm for walking with passive knees. Although many researchers have performed a lot of research regarding the gait planning of the legged robots and have obtained effective planning strategies, the buffer device located at the shin is rarely considered in the gait planning.