Tamio Arai

Multirobot motion coordination in space and time

This paper describes a solution to the multirobot motion planning problem based on a decoupled analysis in the space domain and in the time domain. It investigates the practical use of the notion of motion plan quality and of the motion plan robustness measures for computing safe motions. The use of anytime algorithms allows one to evaluate the opportunity of looking for alternative solution paths by generating small variations of robot motions affecting both its geometrical path and its scheduled velocity. By using the concept of plan robustness, several alternative paths are generated and evaluated through various performance indices and impact factors, using heuristic rules. These indices allow one to know how much a variation affects a given plan. Finally, some recent experiments are outlined.

Cooperative transportation by two four-legged robots with implicit communication

Abstract In this paper, we show cooperative object transportation by two four-legged robots. To realize cooperative transportation with autonomy, we adopt implicit communication based cooperation. Each robot uses only its own sensors to estimate the state of a task. With this method, people can attend to the cooperation system without any changes. We will show an algorithm and two experiments; one is by two legged robots and the other is by one robot and a human.

Environmental support method for mobile robots using visual marks with memory storage

Presents a methodology of environmental support for autonomous mobile robots using visual marks with memory storage. The mark makes up for insufficient function of sensing and recognition; self-positioning, positioning of objects, and deciding methods to operate objects. The mark proposed in this paper consists of a landmark part and a memory part. The landmark part is used to estimate the relative position and orientation between robots and the mark, and the memory part gives information about what it is, what tasks there are, and how to conduct the tasks. Task execution using the marks with real robots is described to show the effectiveness of the proposed methodology.

Local communication of multiple mobile robots: Design of optimal communication area for cooperative tasks

This paper presents an optimal design for local communication between multiple mobile robots. In previous studies of local communication in multirobot systems, the area of communication was not designed using mathematical analysis, but only time-consuming simulations of multirobot communications. We analyzed the information transmission efficiency and created an optimal communication area that minimizes the information transmission time to multiple robots. This optimization comprises two steps. First, we derive the ‘‘information transmission probability’’ for various task models. Next, the derived information transmission probability is used to minimize the information transmission time. The optimal communication design is tested for various tasks, using system parameters. The analytical results are further verified by using computer simulations of multirobot communications and experiments with local communication. Q 1998 John Wiley & Sons, Inc.

Manipulation of multiple objects by two manipulators

This paper focuses on the manipulation of multiple objects, for example, to rake up many objects on a table, lift them up and put them in order, which is difficult to perform for a single manipulator system. This kind of operation becomes possible or much more effective by the cooperation of two manipulators. The lifting up operation of multiple objects by putting them between the two end-effectors is discussed. The use of visual or touch-sensory feedback for the operation, as humans do, cannot prevent the loss of balance for the manipulator system. For the purpose of safe operation, the kinematic analysis and a method of predetermining the pushing force are proposed. The experimental results indicate the effectiveness of the proposed method using simulations with various estimated errors.

Transfer control of a large object by a group of mobile robots

Abstract In this paper, the authors propose a practical cooperative planning architecture of multiple mobile robots by means of a layered architecture consisting of a physical layer, a geometrical layer, and an informational layer. A “Virtual Impedance Model” is used in order to integrate the three layers. The effectiveness of the proposed architecture is verified by experiments and simulations on the task of transferring a large object by multiple mobile robots.

Releasing manipulation with learning control

The properties of releasing manipulation are given. To improve the precision of object posture and decrease trial numbers, two iterative learning control schemes, learning control based on convergent condition (LCBCC), and learning control based on optimal principle (LCBOP) are designed in an experiment-oriented way. These two methods are based on a linearized model. The experimental results show that these methods are effective. After discussing the characteristics of these control methods, we postulate that in the case of where the system does not have enough knowledge, LCBCC is the only choice and to learn system knowledge, after enough experience has been acquired, LCBOP is better than LCBCC, form the view point of convergence rate and precision.

Multiple mobile robot operation by human

We propose an operation method to control mobile robot groups by a single human user, and build a system in which the human user and robots achieve tasks cooperatively. As for the commanding aspect, we divide orders from the user into four levels and consider the relationship between orders and autonomy of robots required. The main features of our method include: 1) the human user commands not just an individual robot, but groups of robots; and 2) our system has autonomy in proportion to user command levels and complements lack of command for the group (sometimes commands for the group is not sufficient for individual robot control). Regarding the monitoring aspect, we introduce a CCD camera system into our system and display information on a CRT display which shows the image of the work area. The user can monitor a remote environment and simultaneously obtain the information needed during operation. We verify the efficiency of our method and system by experiments.

Motion control of cooperative transportation system by quadruped robots based on vibration model in walking

We propose a cooperative transportation method by quadruped robots with vibration in a 3-dimensional environment. In the case of cooperative transportation by legged robots, we must solve two problems; (1) how to avoid exerting excessive internal force on an object and how to deal with sensed values, the position and orientation of the object with vibration because the body of the robot vibrates in walking; and (2) how to decide its velocity that depends on several parameters such as step, walking cycle, and so on. Considering these problems, we construct the cooperation method of the transporting system with vibration. Our method consists of three aspects; firstly we decide how to suitably distribute the objects degree of freedom (DOF) to two quadruped robots. Secondly how to decide the robot velocity is described. Thirdly we create the vibration model aimed at the periodic gait of a quadruped robot by filtering the ingredient of the robot vibration from sensed values of the object deviation from its normal position on the robot. The created model enables us to estimate the deviation of object on the robot and the vibration parameters of the other robot. Moreover, we propose the step prevention motion of quadruped robot where its velocity is close to zero. The effectiveness of the step prevention motion and gait based on the vibration model is verified by some experiments.

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.