Acquisition of Locomotion for Elastic Circular Robot by Using Composite Behavior

A virtual elastic robot as an autonomous robot is proposed which has a body with multiple degrees of freedom. It is capable of fitting its body to the given surrounding environment. This study focuses to allow the elastic robot to adapt to various environments. The intended robot is modeled by rigid objects connected by spring joints in a circular structure. Its control system manipulates spring actuators to realize elastic movements. This paper aims to acquire its control system to the robot to behave autonomously. A behavior acquisition is implemented as an optimization problem by the use of Evolutionary Computation. A physical simulation on the computer is done to achieve given tasks for the virtual elastic robot. The task aims to achieve a locomotion which moves toward a destination on a flat ground. Simulation result shows that the elastic robot acquires a locomotion. Moreover, we assume a complicated circumstance in which an obstacle is put. In order to allow the robot to adapt to a complicated circumstance, a simulation experiment results in forming a behavioral pattern of an autonomous locomotion. These experimental results show that the robot is capable of acquiring locomotion in specific circumstances. I. I NTRODUCTION This study focus on an autonomous robot which is capable of adapting itself to the surrounding environment. An autonomous robot can behave to achieve some tasks. This paper is to acquire their adaptive behaviors that achieve given tasks. Accomplishing this task is regarded as a learning problem for autonomous robots. It has been studied actively in areas such as evolutionary robotics and artificial life. In order to construct an adaptive control system, a bottomup approach is adopted in recent works. This approach aims to construct an optimum control system so as to achieve a given task by a parameter optimization. The parameter optimization is generally implemented by the use of evolutionary computation (EC). There are many studies to acquire autonomous behaviors by computer simulations [1]. K. Sims [1] proposed a method for creating a virtual creature. In this methodology, the geometric morphology for a model structure and a neural system for controlling a creature are both generated automatically using EC. Therefore, it is expected that the creature adapts to the surrounding environment by the use of physical simulation. K. Sims indicated a problem what shape would be the optimum shape to accomplish a task. Similarly, in the area of artificial life, a behavior emergence and an evolution of the artificial creature on a computer become a significant problem. The virtual creature which is proposed K. Sims [1] is expected to design the specialized shape in a specific environment. However, the obtained model cannot exploit its adaptive ability in other environment. Consequently, a modular robot is proposed to solve this problem [2], [3], [4]. The modular robot consists of simple modules, and its behavior is obtained by each module movement based on local communications between connected modules. In many studies, it has seen attracted how to control each module autonomously and emerge its self-reconfigurable property which is capable of changing their module structure by ducking and separation. However, it is not shown how to determine the optimum body structure to adapt to the surrounding environment, like challenges found in the research of K. Sims [1]. Controlling the modular robot is generally studied by the use of a rule-based control which is described by the specific behavior rule for each module [2], [3]. However the rule-based controlling approach has only allowed robots to behave simple motion. Furthermore, it is also difficult to control a model with scalability. Then, an evolutionary heuristic approach is adopted instead of a traditional rule-base approach to control a modular robot [4]. In these background, we have focused on a virtual elastic robot which has a body with multiple degrees of freedom and aimed to acquire behaviors to achieve given tasks [5]. This elastic robot can behave flexibly such as an amoeba and a snake. Especially, the robot is constructed by connecting flexible spring joints. Then a controller to manipulate spring actuators to realize elastic movements is acquired by the use of EC. The body has a circular structure to propagate a elastic motion efficiently. Previously, we have shown that the virtual elastic robot is capable of acquiring locomotive behaviors [5]. This paper aims to reveal a motion mechanism for the obtained behavior. Additionally, in order to adapt the robot to a complicated circumstance, a learning experiment is carried out so as to form a composite behavior by the use of the obtained behavior. The rest of this paper is composed as follows. Section 2 explains some related works. Section 3 proposes an elastic circular robot consisting of modular units. Section 4 describes learning experiment to acquire an autonomous locomotive behavior and shows some experimental results. Section 5 describes a learning experiment to adapt the robot to a circumstance with an obstacle. Section 6 concludes this study with some remarks and gives some directions toward the future work. II. RELATED WORKS There are studies to acquire an amoebic motion by the use of a body with multiple degrees of freedom [6], [7]. A. Ishiguro et al. [6] proposed an amoeboid robot which is connected SCIS & ISIS 2010, Dec. 8-12, 2010, Okayama Convention Center, Okayama, Japan