Daisuke Kurabayashi

Cooperative sweeping by multiple mobile robots

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. For efficient cooperation, setting appropriate burden onto each robot is very important because interference of robots and overlaps of their effecters make efficiency low. The cost of sweeping depends on both sweeping ability of a robot and a shape of a work area to be swept. Evaluation and distribution of the cost are most important issues. In the proposed algorithm, the cost is evaluated by means of length on which robot should move. We introduce both edges of the configuration space and Voronoi diagram so as to compute paths in the whole area. We generate the a tour for traversing all the paths by applying the algorithm of the Chinese Postman Problem. According to the cost evaluation, appropriate paths of the tour are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations and an experiment.

An algorithm of dividing a work area to multiple mobile robots

Proposes an algorithm of dividing a work area into small pieces in order to make multiple mobile robots cooperate efficiently. Searching of a whole work area is the most fundamental and the most essential task of mobile robots. The authors expect that the cost of searching is shared by cooperation of multiple robots. In the proposed algorithm, searching motions of robots are represented by paths. Both edges of the configuration space and the Voronoi diagram are introduced so as to compute paths in the whole area. The authors generate a tour of the paths to traverse all the paths using the algorithm of the Chinese postman problem. The cost is estimated as the total length of the paths. By means of the cost evaluation, the appropriate paths are assigned to each robot. The efficiency of the proposed algorithm is verified by simulations.

A design method of local communication area in multiple mobile robot system

When many mobile robots should achieve cooperation, a local communication system is considered appropriate from the standpoint of the cost and capacity of communication. This paper presents the optimization of the efficiency of local communication in environments where many mobile robots send out information stochastically. The optimal communication area is derived by minimizing the transmission waiting time calculated using the probability of successful information transmission. Computer simulations have been undertaken to verify the analytical results.

Cooperative sweeping by multiple mobile robots with relocating portable obstacles

In this paper, we propose an off-line planning algorithm for cooperative tasks of multiple mobile robots. Sweeping means a motion that a robot covers a 2-dimensional area by its effector. Sweeping of a whole work area is fundamental and essential task of mobile robots. It is more effective if a robot can move an obstacle during a sweeping task as if we clean our room with relocating chairs. We can also consider that this is the simplest task which includes both point-to-point motion and sweeping. We model sweeping and relocation, and propose an algorithm to find appropriate path for robot and way of relocation of each obstacle. We apply the LT graph to solve the problem, which describes both motions of robots and blockades by obstacles in path-time space. We verify the efficiency of the algorithm through simulations and experiments.

Cooperative transport with regrasping of torque-limited mobile robots

This paper deals with a motion planning of mobile robots during the cooperative transport of a large abject by a group of multiple mobile robots (a robot group). In spite of the complexity of the relationship between the several kinds of requirements for this problem, motion planning should be done in real time according to each robots torque limit to apply its force to the object. Based on the algorithm of Ota et al. (1995), the authors propose the following approach: (1) derive handling force applied to the object by each robot, and (2) determine the role for each robot (to handle the object or to regrasp it) by each robots torque limit and optimization of a penalty index indicating performance for obstacle avoidance, stable grasping, and reduction of force. Effectiveness of the proposed method is verified by a transferring simulation.

Evaluating the efficiency of local and global communication in distributed mobile robotic systems

One of the major emerging problems of distributed mobile robotic system is what kind of inter-robot communication to use, because of increasing robots integrated in the system. This paper aims to give an analytical view of this issue. The efficiency of local and global communication is compared based on the analysis of information transmission time to multiple robots. We will show that local communication is effective in environments where cooperative tasks are executed by multiple mobile robots in distributed fashion.

Cooperating grasping of a large object by multiple mobile robots

The authors aim at grasping and handling a large object by cooperating multiple mobile robots with various sizes, moving cost, and load capacity. In this paper the authors focus on the problems of deciding an appropriate grasping arrangement before handling operations. The authors propose this method to avoid bad situations, such as making an object fall down, or some robots overloaded in grasping and handling. The algorithm proposed includes two optimization problems; one is the decision of initial robot arrangement, the other is the decision of final robot arrangement. The difference between these optimizations is that the mass center of the object is recognized or not. The penalty index is defined to minimize the energy the system consumes and to maximize an index of stability. The authors have confirmed that the robots moved to the optimal arrangements in computer simulations and experiments.

Real time planning method for multiple mobile robots

This paper proposes a motion/task planning method for multiple mobile robots. It has two characteristics as follows: (1) facility of implementing tasks, and (2) adapting ability to environment. A layered hierarchical structure is adopted for the proposed planner. The lower layer called virtual impedance method makes a real-time plan to follow the generated trajectory while avoiding obstacles and other robots. The upper layer determines the design parameters of the lower layer which can express motion skills. Simulation results on motion planning and transporting tasks indicate effectiveness of the proposed method.

Dynamic grouping in multiple mobile robots system

A motion planning method for robot groups is presented. First, groups are classified into a group on common partnership (P-group) and a group in shape (cluster) based on types of common factors among members of the same group. The concept of cohesion is proposed to express changeability of clusters. Next, a motion planning method with dynamic grouping, which changes number of cluster in the group based on cohesion, is presented. The approach is implemented using the virtual impedance method. The effectiveness of the method is verified by simulation results.

Iterative Transportation by Cooperative Mobile Robots in Unknown Environment

This paper focuses on a planning method for an iterative transportation task by cooperative mobile robots in an unknown environment. This task requires the acquisition of environmental information, the generation of appropriate robot paths based on the acquired information, and the formation of the group of robots. In order to realize an efficient transportation, a motion planning architecture consisting of ‘environmental exploration phase,’ ‘path-generation phase’ and ‘strategy-making phase’ is proposed. In the first phase, robots explore the environment using a learned visibility graph while transporting. Next, transportation paths consisting of 1-lane paths and 2-lane paths are generated using two kinds of C-spaces. In the final phase, every robot learns a behavior strategy by reinforcement learning and efficient formation of transportation is acquired. Simulation results indicate the effectiveness of proposed architecture.