Ryosuke Chiba

Brainstem control of locomotion and muscle tone with special reference to the role of the mesopontine tegmentum and medullary reticulospinal systems

The lateral part of the mesopontine tegmentum contains functionally important structures involved in the control of posture and gait. Specifically, the mesencephalic locomotor region, which may consist of the cuneiform nucleus and pedunculopontine tegmental nucleus (PPN), occupies the interest with respect to the pathophysiology of posture-gait disorders. The purpose of this article is to review the mechanisms involved in the control of postural muscle tone and locomotion by the mesopontine tegmentum and the pontomedullary reticulospinal system. To make interpretation and discussion more robust, the above issue is considered largely based on our findings in the experiments using decerebrate cat preparations in addition to the results in animal experimentations and clinical investigations in other laboratories. Our investigations revealed the presence of functional topographical organizations with respect to the regulation of postural muscle tone and locomotion in both the mesopontine tegmentum and the pontomedullary reticulospinal system. These organizations were modified by neurotransmitter systems, particularly the cholinergic PPN projection to the pontine reticular formation. Because efferents from the forebrain structures as well as the cerebellum converge to the mesencephalic and pontomedullary reticular formation, changes in these organizations may be involved in the appropriate regulation of posture-gait synergy depending on the behavioral context. On the other hand, abnormal signals from the higher motor centers may produce dysfunction of the mesencephalic-reticulospinal system. Here we highlight the significance of elucidating the mechanisms of the mesencephalic-reticulospinal control of posture and locomotion so that thorough understanding of the pathophysiological mechanisms of posture-gait disorders can be made.

Coordinated motion control of a robot arm and a positioning table with arrangement of multiple goals

The minimum-time motion coordination is an important subject in robotics. In this study, the arrangement of several goals, which is treated as a traveling salesman problem (TSP), is incorporated to this subject. Although TSP has been studied in most previous works; but, solving a TSP that takes into account collision occurrences has not received much attention. This instance arises when a robot arm has to plan a sequence of reaching goals with other moving objects and/or other robot arms. If goals are also moving, then the problem becomes more complex since the end configuration of robot arm is undefined when reaching a goal. In this study, in particular, a 6-DOF robot arm has to reach several goals found in an object while a 1-axis positioning table simultaneously positions the object; thereby changing the goal locations and collision occurrences are inevitable. For the purpose of this study, the TSP is solved effectively with motion coordination and collision avoidance. The collision-free configurations of a robot arm when reaching goals are solved through motion coordination. Collision is avoided by exploiting the redundancy of the system. The above-mentioned solution is verified through a simulation utilizing an object with various numbers of goals and their positions, and is proven effective.

Practical Point-to-Point Multiple-Goal Task Realization in a Robot Arm with a Rotating Table

This study presents a multiple-goal task realization in a system composed of a 6-d.o.f. robot arm and a one-axis rotating table. The problem is complex due to the existence of multiple goals and the kinematic redundancy of the system. We propose a design approach integrating the base placement, task sequencing and motion coordination methods. We show that this approach reduces the task completion time of the robot arm; the motion planning is realized through straight-line paths in the configuration space despite collision occurrences. Furthermore, we introduce a hybrid graph-search method combining the greedy nearest-neighbor method and the Dijkstra method to solve the motion coordination of the robot arm and the table. We show the effectiveness of the design approach and the search method through a time-constrained simulation-based optimization.

Integrated design with classification of transporter routing for AGV systems

This paper presents an integrated design for an automated guided vehicle (AGV) system. Three kinds of integration problems are solved: transporter routings are classified; the number of AGVs for the systems is determined; and suitable flow paths are calculated for the various kinds of transporter routings. The flow paths are calculated by solving an iterative direct problem using a genetic algorithm (GA). The set of transporter routings, the number of AGVs, and the flow path of the AGV systems are constructed with simulations.

Compact design of work cell with robot arm and positioning table under a task completion time constraint

A work cell is generally designed to achieve a high throughput and its size is typically viewed as contingent to component sizes. In this paper, we aim to design a compact work cell (spatial requirement) and to minimize its task completion time (temporal requirement) to a value set as a constraint. By doing so, a work cell occupies a minimal space and achieves its desired throughput. The work cell size is evaluated based on the size and the swept volume of components. This evaluation is important since a robot arm can have a very large swept volume depending on a given task. To satisfy the spatial and temporal requirements, we propose the integration of the base placement optimization, goal rearrangement, and motion coordination between the robot arm and the positioning table. Furthermore, we introduce two motion coordination schemes based on the spatial and temporal requirements. We showed the effectiveness of the proposed method through simulations.

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.

Selection of manipulator system for multiple-goal task by evaluating task completion time and cost with computational time constraints

The focus of this study is on the problem of manipulator system selection for a multiple-goal task by evaluating task completion time and cost with computational time constraints. An approach integrating system selection, structural configuration design, layout design, motion planning, and relative cost calculation is proposed to solve this problem within a reasonable computational time. In the proposed approach, multiple-objective particle swarm optimization (MOPSO) is utilized to search for the appropriate manipulator system with appropriate structural configuration from a set of candidate systems. Particle swarm optimization (PSO) and the nearest neighborhood algorithm are employed in layout design and motion planning due to their high convergence speed. Three methods involving a random search algorithm are compared to the proposed approach through a simulation. The simulation is done with a set of tasks and the result shows the effectiveness of the proposed approach.

Establishment of a function embodiment knowledge base for supporting service design

In service engineering, a service is represented as a functional structure that satisfies customer requirements. Specific entities and their activities are associated with a functional structure as a way to accomplish a goal. In this phase, it is important for service designers to have broad knowledge, since entities that construct a service include both human and physical products. Therefore, the extent of the designer’s knowledge is the key to the enhancement of design solutions. However, few tools to support designers in the embodiment phase have been proposed. In this paper, for the purpose of constructing a function embodiment knowledge base in service design, the representational form of knowledge is proposed, and a prototype system of function embodiment knowledge base is established. Then function embodiment knowledge is collected from multiple service cases using the prototype system, and the effectiveness of knowledge base is discussed.

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.

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.