Jun Ota

Hybrid Design Methodology and Cost-Effectiveness Evaluation of AGV Transportation Systems

In this paper, we analyze and compare the performance of the vertical and the horizontal automated-guided-vehicle transportation systems. We use results in queuing network theory and a transportation simulator to design a hybrid strategy for this study, and to set the appropriate number of agents in the systems. Next, these two transportation systems are evaluated based on cost-effectiveness criteria. For this purpose, the total construction costs of the systems for the various transportation demands are compared. Finally, we provide analytical results to evaluate and to obtain the most efficient system, based on the validity of each system, under different demand scenario. Note to Practitioners-A good design methodology is essential for the study of the optimal layout in an automated container terminal. Port designers need to select the most efficient automated-guided-vehicle (AGV) transportation system, and to set the appropriate number of agents operating in the system. This study presents a hybrid design methodology and a cost-effectiveness comparison of the vertical and the horizontal transportation systems. Our proposed design methodology is able to derive the combinatorial optimal design solutions rapidly, and at the same time pin point the bottleneck in the system. This proposed methodology can be easily applied to any transportation or logistics system, provided the system can be divided into components represented as nodes in a graph. Our results demonstrate that the horizontal AGV transportation system is more effective than the vertical AGV transportation system under most demand scenarios.

Self-calibration of environmental camera for mobile robot navigation

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.

Human upright posture control models based on multisensory inputs; in fast and slow dynamics

Posture control to maintain an upright stance is one of the most important and basic requirements in the daily life of humans. The sensory inputs involved in posture control include visual and vestibular inputs, as well as proprioceptive and tactile somatosensory inputs. These multisensory inputs are integrated to represent the body state (body schema); this is then utilized in the brain to generate the motion. Changes in the multisensory inputs result in postural alterations (fast dynamics), as well as long-term alterations in multisensory integration and posture control itself (slow dynamics). In this review, we discuss the fast and slow dynamics, with a focus on multisensory integration including an introduction of our study to investigate internal force control with multisensory integration-evoked posture alteration. We found that the study of the slow dynamics is lagging compared to that of fast dynamics, such that our understanding of long-term alterations is insufficient to reveal the underlying mechanisms and to propose suitable models. Additional studies investigating slow dynamics are required to expand our knowledge of this area, which would support the physical training and rehabilitation of elderly and impaired persons.

Multiple mobile robot surveillance in unknown environments

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.

Establishment of Social Status without Individual Discrimination in the Cricket

Agonistic behavior in crickets was investigated to understand socially adaptive behavior, which assists with the understanding of the design of an artificial autonomous system in a social organization. Agonistic behavior between male crickets is released by the perception of cuticular substances of conspecific males. The degree of aggressiveness in crickets escalates from antennal fencing to tactical contact until one male quits fighting, at which time social status is established. The question of whether crickets are able to recognize one another to establish social status in an agonist interaction is worthy of pursuit. However, it would be difficult to conduct an experiment to explore this issue while using many individuals. Hence, we examined the social organization among male crickets using a two-step approach: (i) an experiment involving a simulated cricket behavior model and (ii) an experiment involving a behavior experiment using real animals. Our results suggest that crickets establish social status without recognition of their opponents.

Rearrangement Task by Multiple Mobile Robots With Efficient Calculation of Task Constraints

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.

Robust multi-robot coordination in pick-and-place tasks based on part-dispatching rules

This paper addresses the problem of realizing multi-robot coordination that is robust against pattern variation in a pick-and-place task. To improve productivity and reduce the number of parts remaining on the conveyor, a robust and appropriate part flow and multi-robot coordinate strategy are needed. We therefore propose combining part-dispatching rules to coordinate robots, by integrating a greedy randomized adaptive search procedure (GRASP) and a Monte Carlo strategy (MCS). GRASP is used to search for the appropriate combination of part-dispatching rules, and MCS is used to estimate the minimum-maximal part flow for one combination of part-dispatching rules. The part-dispatching rule of first-in-first-out is used to control the final robot in the multi-robot system to pick up parts left by other robots, and the part-dispatching rule of shortest processing time is used to make the other robots pick up as many parts as possible. By comparing it with non-cooperative game theory, we verify that the appropriate combination of part-dispatching rules is effective in improving the productivity of a multi-robot system. By comparing it with a genetic algorithm, we also verify that MCS is effective in estimating minimum-maximal part flow. The task-completion success rate derived via the proposed method reached 99.4% for 10,000 patterns. Propose combination of part-dispatching rules to coordinate multi-robot system.Pattern variation in a pick-and-place task is taken into account.Achieve an appropriate part flow and combination of part-dispatching rules.Integrate a greedy randomized adaptive search procedure with a Monte Carlo strategy.

Design and evaluation of robot patient for nursing skill training in patient transfer

We developed a robot patient for patient transfer training for simulating a patient’s performance during patient transfer and for enabling nurses to practice their nursing skills on it. To realize the robot patient, we focused on addressing the problems of designing its limb actions to enable it to respond to nurses’ operations. RC servos and electromagnetic brakes were installed in the joints to enable the robot to simulate a patient’s limb actions, such as embracing and remaining standing. To enable the robot to automatically respond to nurses’ operations, an identification method for these operations was developed that used voice commands and the features of the limbs’ posture measured by angle sensors installed in the robot’s joints. The robot patient’s performance was examined by a control test in which four experienced nursing teachers performed patient transfer with the robot patient and a human-simulated patient. The results revealed that the robot patient could successfully simulate the actions of a patient’s limbs according to the nursing teachers’ operations and that it is suitable for nursing skill training.

Muscle Activities Changing Model by Difference in Sensory Inputs on Human Posture Control

For understanding of human posture control, changes in muscular activity caused by changes in sensory inputs are very important because the control mechanism is complicated with integrating multi-inputs and outputting various and simultaneous muscular activity. In this research, we aim to obtain quantitative changes in muscular activity caused by changes in sensory inputs. For this purpose, we propose a method to be founded on the idea that muscle activity is divided into external force elements and internal elements. With this method, we can show the existence of internal muscular activity as well as external muscular activity. And it is considered that new model of human posture control with the difference of sensory inputs might be obtained.

Rearrangement task realization by multiple mobile robots with efficient calculation of task constraints

We address a rearrangement task by multiple robot in this paper. A rearrangement task has constraints regarding the order of the start, grasping and finish time. Calculating these constraints has a high computational cost. We propose a rearrangement method that calculates constraints efficiently. In our approach, not all constraints are calculated, but some of them will be calculated step by step. The proposed method is tested in a simulated environment with up to 4 mobile robots. The methods are compared, and the results indicate that the proposed method is superior.