## 1 Introduction
In another work, gait transition using a central pattern generator or CPG was presented [12]. Changes in frequency are applied to CPG to help a robot overcome the limitation on movement due to damage to its body. This method uses multiple chaotic CPGs in conjunction with online learning to let a robot execute fault tolerant movement. The result shows that the robot can move along the desired path and reach its destination. However, the method uses multiple infrared and force sensors for feedback sensing. As a result, it can be applied only in specific scenarios, as reported by [PERSON] et al. in [12]. Most existing methods do not consider legged robots with fewer than four legs. Only the algorithms proposed by [PERSON] et al.and [PERSON] et al. were tested in scenarios in which the robot had only three legs [8; 9]. These methods suffer from a number of pitfalls as mentioned earlier. Moreover, not only the recovery algorithm but also the robot hardware can ensure that the robot remains movable even after sustaining damage, as reported by [PERSON], in which it was suggested that, with hardware improvement, the robot would become more resilient [13]. Because a self-reconfigurable robot can change its structure when it is damaged, structural design is important from the view point of ensuring that the robot can move even after it is damaged. In this study, we focus on two key problems associated with self-recovery robots, namely, robot structure (inspired by caterpillar) and recovery method (inspired by mudskipper). We propose a novel structure of quadruped robots legs based on the behavior of a caterpillar. Caterpillar-like robots have been developed because they can perform not only crawling but also climbing. Caterpillars employ multiple prolegs, to perform crawling, as shown in Figure 1. Because a caterpillar can move forward by using its prolegs to propel its body, this concept is applied to a quadruped robot by using only one leg for motion in the case of damage. However, the structure of the leg must be designed considering the fact that the proleg can limit the reachable space of the robot legs when operating in the normal quadruped gait. In this study, a new shape of robotic legs is designed with the inspiration from caterpillar legs. The Particle Swarm Optimization (PSO) algorithm is employed to optimize the design because the optimized parameter is floating numbers. The fitness function of the PSOis set as the distance that the robot can travel with both crawling and trotting gait. The proposed robotic platform is called Caterpillar-inspired Quadruped Robot or CIQR. The process of design and performance testing are conducted in a simulation environment. The parts of the CIQR are printed using a three-dimensional (3D) printer. Afterward, the performance of the proposed quadruped platform is tested in both simulation and real experiment. Moreover, a new recovery algorithm is also developed in this study. We attempted to use an evolutionary method to find the best action for the damaged robot. A similar approach published by [PERSON] et al. [8] was adopted, but, instead of GA, we applied the PSO algorithm. The reason for using PSO algorithm is that, unlike GA, encoding and decoding processes are not necessary for PSO algorithms. Hence, a new control method based on predefined tasks with a learning method is developed herein. We have designed our algorithm based on mudskippers' behavior. Mudskippers are fish that can crawl on mud with only two fins. We define the mudskipper model to have two degrees of freedom (2-DOFs) and create an action loop with sine and cosine functions. Additionally, the Q-learning method is integrated with mudskipper-inspired behavior to enable the robot to move faster in a more efficient manner. Both numerical simulation and practical experiment with a CIQR are conducted to test the performance of proposed recovery algorithm. The rest of the paper is organized as follows. Section 2 describes the development of a new structural design of a quadruped robot.