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If we define a mode as a set of specific configurations that hold the same constraint, and if we investigate their transitions beforehand, we can efficiently probe the configuration space by using a manipulation planner. However, when multiple mobile robots together manipulate an object by using the non-prehensile method, the candidates for the modes and their transitions become enormous because of the numerous contacts among the object, the environment, and the robots. In some cases, the constraints on the object, which include a combination of robot contacts and environmental contacts, are incapable of guaranteeing the object's stability. Furthermore, some transitions cannot appear because of geometrical and functional restrictions of the robots. Therefore, in this paper, we propose a method to narrow down the possible modes and transitions between modes by excluding the impossible modes and transitions from the viewpoint of statics, kinematics, and geometry. We first generated modes that described an object's contact set from the robots and the environment while ignoring their exact configurations. Each multi-contact set exerted by the robots and the environment satisfied the condition necessary for the force closure on the object along with gravity. Second, we listed every possible transition between the modes by determining whether or not the given robot could actively change the contacts with geometrical feasibility. Finally, we performed two simulations to validate our method on specific manipulation tasks. Our method can be used in various cases of non-prehensile manipulations by using mobile robots. The mode transition graph generated by our method was used to efficiently sequence the manipulation actions before deciding the detailed configuration planning. [ABSTRACT FROM AUTHOR]

In the past few decades, simulation training has been used to help nurses improve their patient-transfer skills. However, the effectiveness of such training remains limited because it lacks effective ways of simulating patients’ actions realistically. It is difficult for nurses to use the skills learned from simulation training to transfer an actual patient. Therefore, we developed a robot patient that could simulate the behavior of patients’ limbs for patient-transfer training. This study examined the performance of the robot used in training and evaluated its training effectiveness. Four nursing teachers individually transferred the robot patient and then scored the robot patient's ability to simulate patients’ actions and its suitability for skill training. An experiment using pre-post control group design was carried out to examine the robot patient's training effectiveness compared with the human simulated patient. The participants were 20 nursing students and one nursing teacher who was responsible for scoring the students’ skills in the pre-test and post-test. All of the students were assigned to train with either the proposed robot patient or a healthy person simulating the patient. The results show that all four nursing teachers regarded the robot patient's actions as realistic. In addition, all four teachers agreed that the robot patient was suitable for skill training. The results also show that the proposed robot patient is more challenging than the current method, which employs a healthy person to simulate the patient. Significant skill improvement (p < 0.01) was observed in the experimental group when transferring the robot patient. [ABSTRACT FROM PUBLISHER]

In this paper, we have dealt with the problem to transport large heavy objects using a group of small mobile robots. Generally, payload of the robot, the maximum weight of the object that the robot can operate, is very small and they cannot transport heavy objects with standard coordinated grasping methodology. This paper considers a method of transporting an object using handcarts by tilting the object to load it on the handcarts. To resolve the problem of avoiding overturning of the object by the robots and sliding of the handcart while tilting the object, an outrigger device is used to prevent the first problem of tilting, and a handcart locking device is used to prevent the second problem of sliding. As both devices need to be used only when necessary, a mechanism that can fix and release the devices according to situations is newly designed. Two robots were trial fabricated: an object-tilting robot equipped with an outrigger mechanism and a handcart transport robot to handle the handcarts. Both robots are smaller than 0.6 m × 0.6 m with payload of 2.5 kg. They are equipped with a handcart mechanism that can be locked and unlocked. The use of the coordination and lock mechanisms by these robots has realized transport of objects approximately 1 m high and weighing approximately 35 kg and demonstrated the effectiveness of the proposed system in a real-world environment where robot mechanism errors, mobility errors, and observation errors occur. [ABSTRACT FROM AUTHOR]

In this paper, we present a strategy for fast grasping of unknown objects based on the partial shape information from range sensors for a mobile robot with a parallel-jaw gripper. The proposed method can realize fast grasping of an unknown object without needing complete information of the object or learning from grasping experience. Information regarding the shape of the object is acquired by a 2D range sensor installed on the robot at an inclined angle to the ground. Features for determining the maximal contact area are extracted directly from the partial shape information of the unknown object to determine the candidate grasping points. Note that since the shape and mass are unknown before grasping, a successful and stable grasp cannot be in fact guaranteed. Thus, after performing a grasping trial, the mobile robot uses the 2D range sensor to judge whether the object can be lifted. If a grasping trial fails, the mobile robot will quickly find other candidate grasping points for another trial until a successful and stable grasp is realized. The proposed approach has been tested in experiments, which found that a mobile robot with a parallel-jaw gripper can successfully grasp a wide variety of objects using the proposed algorithm. The results illustrate the validity of the proposed algorithm in term of the grasping time. [ABSTRACT FROM AUTHOR]

In this paper, we present a strategy for fast grasping of unknown objects by mobile robots through automatic determination of the number of robots. An object handling system consisting of a Gripper robot and a Lifter robot is designed. The Gripper robot moves around an unknown object to acquire partial shape information for determination of grasping points. The object is transported if it can be lifted by the Gripper robot. Otherwise, if all grasping trials fail, a Lifter robot is used. In order to maximize use of the Gripper robot’s payload, the detected grasping points that apply the largest force to the gripper are selected for the Gripper robot when the object is grasped by two mobile robots. The object is measured using odometry and scanned data acquired while the Gripper robot moves around the object. Then, the contact point for calculating the insert position for the Lifter robot can be acquired quickly. Finally, a strategy for fast grasping of known objects by considering the transition between stable states is used to realize grasping of unknown objects. The proposed approach is tested in experiments, which find that a wide variety of objects can be grasped quickly with one or two mobile robots. [ABSTRACT FROM AUTHOR]

A rearrangement problem involving multiple mobile robots is addressed in this paper. In the problem, it is important to identify task decomposition, task allocation, and path planning applicable to distinct environments while rearrangement tasks are executed. We here define ‘task apportionment’ as an operation that sets up task decomposition and conducts task allocation based on that setup. We propose a method for task apportionment and path planning applicable to distinct environments. The method establishes the necessary intermediate configurations of objects as one way of task decomposition and determines task allocation and path planning as a semi-optimized solution by using simulated annealing. The proposed method is compared with a continuous transportation method and a territorial method through simulations and experiments. In the simulations, the proposed method is, on the average, 17 and 20% faster than the continuous transportation method and the territorial method, respectively. In the experiments, the proposed method is, on the average, 22 and 16% faster than the continuous transportation and the territorial method, respectively. These results show that the proposed method can realize an efficient rearrangement task by mobile robots in various working environments under feasible computation time, especially in environments with a mixture of wide and narrow areas and an uneven distribution of objects. [ABSTRACT FROM PUBLISHER]

Fast transition from a stable initial state to a stable handling state is important when multiple mobile robots grasp and transport a bulky and heavy object. In this paper, we present motion planning for two robots of an irregularly shaped object handling system considering fast transition between stable states. A cooperative object handling system consisting of a gripper robot equipped with a gripper and a lifter robot equipped with a lifter was first designed. Then, a strategy to realize fast transition between stable states by using the object handling system designed was proposed. While grasping and lifting an object off the ground, a gripper robot grasps and lifts up the object from one side to provide enough space for a lifter robot to lift the object off the ground cooperatively. Fast transition between stable states is formulated as a constraint optimization problem. The goal is to realize transition from a stable initial state to a stable handling state in a minimal amount of time. Experiments involving two robots and everyday objects were conducted. The two robots cooperatively obtained fast transition between stable states. The results illustrate the validity of the proposed method. [ABSTRACT FROM PUBLISHER]

In this paper, we address a rearrangement task planning problem. The method proposed here is suitable for various environments with narrow corridors, and an unbalanced arrangement of robots and objects. As the solution space is too large for the search method to be applied directly, we will limit the search space. The proposed method develops an initial plan by using a simple rule and improves the task decomposition of the initial plan. That is, it effectively determines which object should be transported where. We employ the concept of the critical path method to select the task that should be modified and the concept of a territorial approach to set up new task decomposition. New task decomposition is set up so that a robot can operate without considering the movement of other robots. These concepts render our method fast. The proposed method is tested in a simulated environment with up to four robots and 12 movable objects. The simulation results show that in a feasible calculation time, our method can reduce the task time by 10% as compared to the previous method. In particular, the proposed method is much more applicable to the working environments than was the previous method. [ABSTRACT FROM AUTHOR]

In this paper, we address a multiple robot rearrangement problem. For different applications, problem-solving methods should be able to cope with various working environments. We focus on small working environments in particular with a concentrated arrangement of objects and narrow corridors. In this type of environment, the rearrangement problem can be very complicated because of high computational cost for priority settings to prevent robots from colliding and constraints related to the order of transportation. We propose a practical algorithm that divides a complicated rearrangement problem into simple subproblems. In our method, the rearrangement problem can be reduced to a project scheduling problem using a territorial approach. The application of a territorial approach can relax the complexity of priority settings, but yields new kinds of constraints at the same time. We propose an extended project scheduling problem solver to address these constraints. The solver is constructed on the basis of meta-heuristic strategy and generates the order of transportation that observes constraints. The proposed method is tested in a simulated environment with up to four mobile robots and 12 movable objects. Simulation results show the effectiveness of our method with respect to the applicability and a reasonable calculation time. [ABSTRACT FROM AUTHOR]

A rearrangement planning methodology of multiple movable objects by a mobile robot is proposed for a certain rearrangement problem, i.e., the LPεk (k > 2) problem. Several objects are to be moved from an initial configuration to separate destinations as a result of a robot handling operation. Proposed in this paper is a planning algorithm consisting of a global motion planner and a local motion planner. The global planner uses a precedence graph of a movable object, while the local planner uses a real-time search methodology called LRTA* (Learning Real-Time A*). Two important factors in the local planner are the generation of intermediate configurations and the design of heuristic functions. Three methods in each factor are compared in the rearrangement simulation of four, seven and 10 movable objects. The proposed method demonstrates the effectiveness of the proposed algorithm from the viewpoint of task completion time. The calculation costs for both planners are polynomial with the number of movable objects for one time activation. Simulation results indicate that the proposed algorithm can be practically applied, although not complete, to rearrangement problems with, at most, about 10 movable objects. [ABSTRACT FROM AUTHOR]

We address multiple-robot rearrangement problems in this paper. The rearrangement of multiple objects is a fundamental problem involved in numerous applications. In this case, it must be considered that a rearrangement task has constraints regarding the order of the start, grasping and finish time of transportation. Attention to these constraints makes it possible to rearrange rapidly; however, the calculation of the constraints is costly in terms of computation. In this paper, we propose a rearrangement method that calculates constraints efficiently. We analyze constraints and classify them into two groups: those that require less computational cost and those that require more. Robots do not calculate all groups at the same time — the time required for each type of calculation varies. The proposed method is tested in a simulated environment 96 times in six kinds of working environments with up to four mobile robots. Compared to the method that calculates all constraints at the same time, the robots' inactive time is significantly reduced and the total time for task completion is also eventually reduced. The proposed method is incomplete, but can be used to perform most rearrangement problems in a short time. [ABSTRACT FROM AUTHOR]

This research aims to deal with the fundamental problems that arise in surveillance missions in complex environments in which a distributed multiple robot system is operating. In this research, task means the surveillance mission of the multiple robot system. The system-level task can be retrieved using the Reaction–Diffusion Equation on a Graph-based surveillance strategy planner. The task is the combination of observation points that the robots have to visit in order to gain complete information about the target environment. This paper contains several examples of methods used for task decomposition and allocation in surveillance tasks undertaken by multiple mobile robots. In an indoor environment, a robot group is first sent out in an exploration phase by the proposed distributed sensing and complete coverage strategy. The surveillance mission requires the iterative search of events over and over in the target environment. In the iterative surveillance operation, the robots monitor their individual coverage areas and update their local maps to account for environmental changes such as changes in position of authorized equipment, vehicles, etc. In order to quickly respond to such changes, in this research, the shortest cyclic path is aimed as a result of the iterative surveillance path. The shortest iterative surveillance path results in complete coverage of the target area at as a high a frequency as possible and maximum area covered in unit time. [ABSTRACT FROM AUTHOR]

A simple interface is described that makes it easier for operators of mobile robots to use multiple images provided by distributed cameras. While the images provided by multiple cameras located on ceilings or walls can provide global position information for use in navigating mobile robots, a human operator must be able to understand the working area by observing the multiple images, which is burdensome. Accounting for this, we propose a simple interface for operating the mobile robot through multiple camera images. To assist human recognition of the relationship between multi-displayed images from cameras located in unknown wide working areas, we designed and implemented the interface to have the following main features: (i) indication of overlap areas from cameras to support human recognition of working areas and (ii) indication of rough routes for robot navigation to assist robot operation from captured images. The effectiveness of the interface and that of the entire robot system were demonstrated experimentally. [ABSTRACT FROM AUTHOR]

This paper offers a proposal for realizing the exploration and rearrangement of multiple unknown objects that lay scattered in working environments. The objective of the exploration task is to find all the objects in the environments. On the other hand, the objective of the rearrangement task is to carry all the objects to their goal position. Many applications are possible if the exploration and rearrangement tasks are combined. Some of them are cleaning, mine detecting and housework. An algorithm that integrates two tasks is presented with respect to the effectiveness of the path length and computational cost. In addition, an exploration algorithm is proposed that can work well in an environment that has many objects. In order to verify the algorithm, experiments are conducted with an actual robot. In the experimentals, an environmental recognition method is developed by attaching a mark to the objects. The robot recognizes the objects by finding the mark. It then obtains information from the mark. The mark is also used to modify the odometry error of the robot by computing its configuration relative to a mark attached to a wall. The success rate of this experiment was almost 80% in 20 trials. [ABSTRACT FROM AUTHOR]

In this paper, we present a method to generate exploration path for multiple mobile robots in a restricted working area. In exploration mission by mobile robots, the goal is to minimize the overall exploration time and ensure a thorough exploration. The key problem to be solved is to generate effective exploration paths so that mobile robots share their exploration regions in a working area. During the exploration, in situations in which new obstacles are detected on the paths or some observation points are not reachable by a mobile robot, the generated paths will not permit a thorough exploration. New paths that can ensure thorough exploration must accasionally be re-planned. The method proposed here should re-plan paths with low computational cost. The proposed method is realized by the combination of (a) deployment of the observation points in a working area using a reaction-diffusion equation on a graph, and (b) clustering the observation points to generate exploration paths that have a uniform path length for each mobile robot. Using reaction-diffusion equation on a graph in an observation point deployment will decentralize the computation of each observation point position. The efficiency and robustness of the proposed method are evaluated in simulations and in real exploration missions by two mobile robots in indoor environments. [ABSTRACT FROM AUTHOR]

In this paper, we propose a motion-planning method of multiple mobile robots for cooperative transportation of a large object in a three-dimensional environment. This task has various kinds of problems, such as obstacle avoidance and stable manipulation. All of these problems cannot be solved at once, since it would result in a dramatic increase of the computational time. Accordingly, we divided the motion planner into a global path planner and a local manipulation planner, designed them, and integrated them. The aim was to integrate a gross motion planner and a fine motion planner. Concerning the global path planner, we reduced the dimensions of the configuration space (C-space) using the feature of transportation by mobile robots. We used the potential field to find the solution by searching in this smaller-dimension reconstructed C-space. In the global path planner, the constraints of the object manipulation are considered as the cost function and the heuristic function in the A[sup *] search. For the local manipulation planner, we developed a manipulation technique, which is suitable for mobile robots by position control. We computed the conditions in which the object becomes unstable during manipulation and generated each robot's motion, considering the robots' motion errors and indefinite factors from the planning stage. We verified the effectiveness of our proposed motion planning method through simulations. [ABSTRACT FROM AUTHOR]

In this paper, the novel idea of using an autonomous mobile robot as a virtual local network is proposed as a system for the remote diagnosis of faults of a mobile robot. There are two primary points in this research. First, an objective of the research is to achieve a system with good expandability, i.e. one in which the diagnosis can be achieved whether there are many or few mobile robots to be diagnosed. To accomplish this goal by simply changing some system settings, a simple network management protocol (SNMP) structure is utilized. Within the developed diagnosis system, a mobile robot is taken as one of the management objects of the network management system (NMS). The SNMP, which is widely used in the NMS, is applied and adapted to the developed system as the communication protocol for exchanging diagnosis information. Moreover, by taking advantage of the active moving and sensing ability of autonomous mobile robots, an effective method of fault inference called a 'run-test' is discussed. By using this method, the accuracy of the diagnoses is improved. In the best-case scenario, the certainty of an accurate diagnosis increased from 20% (without using the 'run-test') to 93%. On the other hand, in some cases, the accuracy of the diagnosis results barely improved. On average, among the cases discussed in this paper, the accuracy of the diagnosis results improved about 2.1 times by the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in an unknown static environment. The architecture should satisfy three features: deal with a variety of tasks in time and space, deal with a large number of tasks compared with the number of robots, and decide behavior in real time. The authors propose the following approach: We consider the unit of task (task instance) as the job that should be done in a short time by one robot. Based on environmental information, task instances are dynamically generated using task templates. The priority of task instances is evaluated dynamically based on the number of robots and the configuration in the workspace. In addition, we avoid generating too many task instances by suppressing object motion. The main part of the architecture consists of two real-time planners: a priority-based task-assignment planner solved by using a linear programming method, and motion planners based on short-time estimation. The effectiveness of the proposed architecture is verified by a cooperative transport simulation in an unknown environment. [ABSTRACT FROM AUTHOR]

Until now, we have been developing a system for multiple mobile robot operation by a single human operator. In order that robots may achieve tasks in unknown environments, research focusing on the following three points must be conducted: 1) design of commands from the operator to the robots; 2) environmental recognition to show the operator information about the remote work area where robots are working; and 3) interface between a system and the operator and information display of the work area for the operator. For 1), the focus is on the operation of the multiple robots by a single operator. Orders from the operator are divided into several levels and the relationship between the orders and the necessary autonomy of the robots are considered. For 2), the problem is divided into two parts; object recognition and self-positioning. Concerning the former, stereovision is used. Two robots, each equipped with a monocular camera, acquire a three-dimensional position of a point on the surface of an object within an environment. As for the latter, markers are placed on the robots so that their relative positions can be measured. As for 3), Graphical User Interface (GUI) is implemented. The operator mainly uses a mouse to input commands, and the operator watches a virtual environment to monitor remote working areas. The virtual environment is constructed with the environment information acquired by the method described in 2) above. After the problems mentioned above are solved, our system will provide a flexible command and monitoring structure and an operator would be able to command the robots appropriately. These are the main advantages of the method we are proposing. We verified the effectiveness of the proposed methods in experiments. [ABSTRACT FROM AUTHOR]

Service robots are frequently fitted with end-effecters, which require high energy, to achieve a specific task. Robots require high-power energy sources that can meet several goals simultaneously. Given the technology of today, a battery-driven robot cannot work for long on a single charge. Todevelop a new powerful battery technology may take many years of exhaustive research. In this paper, we present a dual-energized scheme called HYbrid POwer Supply (HYPOS) that integrates the function of batteries and a household electric system to supply a robot. This technique can be realized by existing technology and is applicable to a variety of indoor applications. The challenge of implementing the HYPOS system is to develop the outlet-connection procedures and to handle the electric cord to reduce movement disturbance. We report on the prototype robot and the experiments that illustrate the effectiveness and practicality of this proposed system. The result has shown that the HYPOS system can supply a robot consecutively for almost 2 h and its efficiency is 73.6%, while the efficiency of a lead-acid battery is only 38.5%. [ABSTRACT FROM AUTHOR]

Discusses a study that investigated the effectiveness of 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. Details on the use of a virtual impedance model to integrate the three layers; Tasks of multiple mobile robots; Conclusion.

Deals with how to introduce motion skills in the motion planning of multiple mobile robots. Definition of the motion skills as rules of `IF (a specific situation) THEN (a specific manner of motion)' type; Introduction of the concept of sensor information pattern; Acquisition of the motion skills by induction process.

Investigates the group intelligence of multiple mobile robots. Use of the analogy of dwarves in fairy tales to discuss cooperation and to classify it into three levels; Behavior via on-line motion planning; Examples of cooperation using Virtual Impedance Method; Mutual relationships among robots and environments; Cooperative handling of a large object by a group of mobile robots.

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. © 1998 John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Deals with a study which examined a task-assignment architecture for cooperative transport by multiple mobile robots in unknown environment. Description of a material handling system by a group of mobile robots that works in a coordinated manner; Data and methods; Results and suggestions.

An environmental camera is a camera embedded in a working environment to provide vision guidance to a mobile robot. In the setup of such robot systems, the relative position and orientation between the mobile robot and the environmental camera are parameters that must unavoidably be calibrated. Traditionally, because the configuration of the robot system is task-driven, these kinds of external parameters of the camera are measured separately and should be measured each time a task is to be performed. In this paper, a method is proposed for the robot system in which calibration of the environmental camera is rendered by the robot system itself on the spot after a system is set up. Specific kinds of motion patterns of the mobile robot, which are called test motions, have been explored for calibration. The calibration approach is based upon executing certain selected test motions on the mobile robot and then using the camera to observe the robot. According to a comparison of odometry and sensing data, the external parameters of the camera can be calibrated. Furthermore, an evaluation index (virtual sensing error) has been developed for the selection and optimization of test motions to obtain good calibration performance. All the test motion patterns are computed offline in advance and saved in a database, which greatly shorten the calibration time. Simulations and experiments verified the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract This study proposes a mechanism and a methodology for large force input to the environment by a mobile robot. To determine the limits on the force that a mobile robot can apply to a target object, we analyzed the forces between the robot, ground, and object, and the frictional-force limits between any two of these three bodies. To prevent the mobile robot from falling during the large-force application, the manipulator is connected to the robot via a passive rotational joint. This mechanism enables the mobile robot to search the environmental parameters. A new mobile robot fitted with the proposed mechanism, named ARODA, was developed. In a validation experiment, the developed mobile robot successfully tilted a relatively large and heavy object while searching the environmental parameters (the frictional coefficients of the floor and object and the size of the object). Equipped with the proposed mechanism, the mobile robot refrained from falling while applying a large force to the object by trial and error. Highlights • A mechanism for a mobile robot to apply a large force without falling is proposed. • The mobile robot with the proposed mechanism named ARODA is developed. • The ARODA successfully tilted a heavy object while searching the unknown parameters. [ABSTRACT FROM AUTHOR]