Akiya Kamimura

M-TRAN: self-reconfigurable modular robotic system

In this paper, a novel robotic system called modular transformer (M-TRAN) is proposed. M-TRAN is a distributed, self-reconfigurable system composed of homogeneous robotic modules. The system can change its configuration by changing each modules position and connection. Each module is equipped with an onboard microprocessor, actuators, intermodule communication/power transmission devices and intermodule connection mechanisms. The special design of M-TRAN module realizes both reliable and quick self-reconfiguration and versatile robotic motion. For instance, M-TRAN is able to metamorphose into robotic configurations such as a legged machine and hereby generate coordinated walking motion without any human intervention. An actual system with ten modules was built and basic operations of self-reconfiguration and motion generation were examined through experiments. A series of software programs has also been developed to drive M-TRAN hardware, including a simulator of M-TRAN kinematics, a user interface to design appropriate configurations and motion sequences for given tasks, and an automatic motion planner for a regular cluster of M-TRAN modules. These software programs are integrated into the M-TRAN system supervised by a host computer. Several demonstrations have proven its capability as a self-reconfigurable robot.

Automatic locomotion design and experiments for a Modular robotic system

This paper presents a design method and experiments for whole-body locomotion by a modular robot. There are two types of locomotion for modular robots: a repeating self-reconfiguration and whole-body motion such as walking or crawling. For whole-body locomotion, designing a control method is more difficult than for ordinary robots because a modular robotic system can form various configurations, each of which has many degrees of freedom. This study proposes a unified framework for automatically designing an efficient locomotion controller suitable for any module configuration. The method utilizes neural oscillators (central pattern generators, CPGs), each of which works as a distributed joint controller of each module, and a genetic algorithm to optimize the CPG network. We verified the method by software simulations and hardware experiments, in which our modular robotic system, named M-TRAN II, performed stable and effective locomotion in various configurations.

Distributed Self-Reconfiguration of M-TRAN III Modular Robotic System

A new prototype of a self-reconfigurable modular robot, M-TRAN III, has been developed, with an improved fast and rigid connection mechanism. Using a distributed controller, various control modes are possible: single-master, globally synchronous control or parallel asynchronous control. Self-reconfiguration experiments using up to 24 modules were undertaken by centralized or decentralized control. Experiments using decentralized control examined a modular structure moved in a given direction as a flow produced by local self-reconfigurations. In all experiments, system homogeneity and scalability were maintained: modules used identical software except for their ID numbers. Identical self-reconfiguration was realized when different modules were used in initial configurations.

A Self-Reconfigurable Modular Robot

In this paper we address a reconfiguration planning method for locomotion of a homogeneous modular robotic system and we conduct an experiment to verify that the planned locomotion can be realized by hardware. Our recently developed module is self-reconfigurable. A group of the modules can thus generate various three-dimensional robotic structures and motions. Although the module itself is a simple mechanism, self-reconfiguration planning for locomotion presents a computationally difficult problem due to the many combinatorial possibilities of modular configurations. In this paper, we develop a two-layered planning method for locomotion of a class of regular structures. This locomotion mode is based on multi-module blocks. The upper layer plans the overall cluster motion called flow to realize locomotion along a given desired trajectory; the lower layer determines locally cooperative module motions, called motion schemes, based on a rule database. A planning simulation demonstrates that this approach effectively solves the complicated planning problem. Besides the fundamental motion capacity of the module, the hardware feasibility of the planning locomotion is verified through a self-reconfiguration experiment using the prototype modules we have developed.

Self-reconfigurable modular robot - experiments on reconfiguration and locomotion

We have proposed a self-reconfigurable robotic module, which has a very simple structure. The system is capable of not only building a static structure, but also generating a dynamic robotic motion. We have also developed a simulator for the motion planning. In this paper, we present details of the mechanical and electrical designs of the developed module and its control system architecture. Experiments using ten modules demonstrate the robotic configuration change, crawling locomotion and three types of quadruped locomotion.

M-TRAN II: metamorphosis from a four-legged walker to a caterpillar

We have been developing a self-reconfigurable modular robotic system (M-TRAN) which can make various 3-D configurations and motions. In the second prototype (M-TRAN II), various improvements are integrated in order to realize complicated reconfigurations and versatile whole body motions. Those are a reliable connection/detachment mechanism, on-board multi-computers, high speed inter-module communication system, low power consumption, precise motor control, etc. Programing environments are also integrated to design self-reconfiguration processes, to verify motions in dynamics simulation, and to realize distributed control on the hardware. Hardware design, developed software and experiments are presented in this paper.

Automatic locomotion pattern generation for modular robots

Locomotion, one of the most basic robotic functions, has been widely studied for several types of robots. As for self-reconfigurable modular robots, there are two types of locomotion; one type is realized as a series of self-reconfiguration and the other is realized as a whole body motion such as walking and crawling. Even for the latter type of locomotion, designing control method is more difficult than ordinary robots. This is because the module configuration includes many degrees of freedom and there are a wide variety of possible configurations. We propose an offline method to generate a locomotion pattern automatically for a modular robot in an arbitrary module configuration, which utilizes a neural oscillator as a controller of the joint motor and evolutionary computation method for optimization of the neural oscillator network, which determines the performance of locomotion. We confirm the validity of the method by software simulation and hardware experiments.

A motion planning method for a self-reconfigurable modular robot

This paper addresses motion planning of a homogeneous modular robotic system. The modules have self-reconfiguration capability so that a group of the modules can construct a robotic structure. Motion planning for self-reconfiguration is a kind of computationally difficult problem because of many combinatorial possibilities of modular configuration and the restricted degrees of freedom of the module; only two rotation axes per module. We will show a motion planning method for a class of multimodule structures. It is based on global planning and local motion scheme selection that is effective to solve the complicated planning problem.

Distributed adaptive locomotion by a modular robotic system, M-TRAN II

A modular robot has a distributed mechanical composition which can make various configurations and also make locomotion in a wide variety of configurations. Modular robots are thought to be useful in extreme or unknown environments by adaptively changing their shape and locomotion patterns. As for locomotion, two types can be used; one is whole-body fixed-configuration locomotion and the other is locomotion by self-reconfiguration. In this paper we deal with the former type of locomotion which is realized by coordinated joint actuation. So far, proposed control methods for whole-body locomotion by modular robots have been based on predefined locomotion sequences. However, locomotion based on predefined sequences cannot adapt to changing terrain conditions such as uphill, downhill, slippery and sticky grounds. To solve such problems, we propose a distributed control mechanism using a CPG controller which enables adaptive locomotion by modular robots. Besides the real-time CPG control we introduce a decentralized control mechanism for detecting the situation that the robot is stuck and initiating transformation to another shape for recovering the situation. The results of various hardware experiments by 4-legged structure prove the feasibility of the method for adaptive locomotion and transformation by our M-TRAN II modules.

Self-reconfigurable M-TRAN structures and walker generation

Abstract The M-TRAN is a modular robot capable of both three-dimensional self-reconfiguration and whole body locomotion. Introducing regularity in allowed structures reduced difficulties of its reconfiguration problems. Several locomotion patterns in various structures were designed systematically using a CPG controller model and GA optimization. Then they were verified by experimentation. Results showed a feasible scenario of operation with multiple M-TRAN modules, which is presented herein, including metamorphosis of a regular structure, generation of walkers from the structure, walker locomotion, and reassembling of walkers to the structure.