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Recently, cooperation between robots attract attention as a method to realize advanced task that cannot be realized with single robot. However, in previous cooperation between robots, information to share is usually restricted to single modality. Therefore, we suggest a method of sharing various types of information to realize cooperation between multi-modality. With this method, peculiar information that cannot share are changed into the abstract hierarchy that the different type modality robot is able to share such as numerical value and the name label. In this paper, we assumed a garbage collection task as an example of cooperative tasks and design a system that integrates a vision based system with a sound based system. This integrated system execute a task by visual information to find a task by audiory information. We demonstrated availability of proposed method and visual-audio system by experimental result.

This paper proposes a cooperative visual object tracking by multi-robot system, where robust cognitive sharing is essential between the robots. However, one of the main issues in vision-based distributed observation is the significant differences in the background image for the interested object. According to the observing point of the robot, effective invariant feature to identify the interested object is different. In this paper, we propose an ambiguity index to select better feature algorithm for object tracking. Experimental result shows promising result for the effective multi-robot cognitive sharing.

This section introduces brachiation robots that are monkey-type robots developed previously in our laboratory as one of bio-inspired robots. In pioneering research, the dynamics of locomotion were analyzed and locomotion types proposed using a six-link brachiation robot [64]. Following this research, the second one is a two-link brachiation robot “Brachiator II” shown in Fig. 3.1. This robot has one actuator at the elbow connecting two links, each of which has a gripper. Because the gripper cannot impose torque on the handhold directly, this is an underactuated mechanical system. We developed a two-link brachiation robot and proposed a heuristic method to find feasible motions [67, 244, 245].

In this chapter, we aim to realize robust locomotion in unknown test courses, so robots recognize a slope or a step and plan to locomotion. In the next place they need to know whether they realize the plan or not. In robotics system there is uncertainness. Since it influence on realization of performance, we have to deal with uncertainty. This uncertainty is classified into four categories. First one is the uncertainty caused by motion. For example, it’s approximation of motion algorithm. Most robots have models to simplify calculating dynamics. So this gives robot systems uncertainty because there are difference between a reality robot shape and a robot model. Second uncertainty is about recognition is accuracy of sensors, effective ranges of sensor or abstraction of environment. Third uncertainty comes from controller (software). If the controller is not good for robot motion, the robot has a lot of error in moving. And fourth uncertainty is about hardware. For example, reliance on consumption of motor or breakdown of motor, and reliance on sensors with noise have uncertainty. In this chapter, we propose the way of estimation of uncertainty in robot system by use of the Bayesian Networks. Uncertainty in robot system limits robot locomotion modes. And robot can get adaptation to environmental or conditions.

Miura et al.[183] and Furusho et al.[75] 3-D motion was divided into a pair of planes—lateral plane and sagittal plane—and built the controller based on the lateral and sagittal dynamics. The lateral plane is defined as an Addison’s clinical plane passing vertically on either side through a point on the interspinal halfway between the anterior portion of the iliac crest and the median plane. Meanwhile, the sagittal plane is defined as a longitudinal plane that divides the body of a bilaterally symmetrical animal into right and left sections. This dividing is based on the following two assumptions: 1) The motion in each plane is small—i.e. the amplitude of lateral motion is small and step-length in the sagittal plane is relatively short—enough that the effects of each plane on each other is low. 2) The motion in each plane is stable against disturbance generated by motion in other plane.

The pitch and roll joints which is used for this ladder climbing locomotion are shown in Fig. 6.1(a). The idlling arm and leg motion are designed in sagittal plane for avoiding the collision with any rungs.

This paper deals with a cooperative object tracking with mobile robotic sensor network. The occlusion problem, which is one of the most important problems of mobile object tracking, will be solve with utilizing the mobile robotic sensor network. Additionally, the high quality information of the object can be observed, since the robotic sensor network can change observation formation their own way. On the other hand, to solve these problems the high cognitive capability and high intelligence sharing ability of robots are required. Consequently, we propose to use high intelligent group robot each of which can communicatewith Peer-to-Peer communication. The self-deployment algorithm and network routing algorithm are developed as a base technic of mobile sensor network. The validity of these proposed algorithms are shown by multihop teleoperation experiment. The architecture to share common perceptions which is necessary for cooperative work are proposed.

A great deal of information and traffic circulate over the complex and largescale networks. Such examples abound in an airline route or road map, and the Internet web[1]. These are important social infrastructures and hence desired to possess sufficient resilience against an unpredictable breakdown in order to maintain the expected function. Including redundant nodes and links to the network is expected to allow more robust systems, however it would make the system more expensive and less efficient in the ordinary situations. Therefore, a well-balanced network topology taking into account both optimality and resilience is of great importance[2]. Recently, it has come to be known that a number of real world networks are scale-free network (SFN), as seen in the airline route map, electrical power network, and the Internet web[3, 4, 5]. One of the main features in SFN is that the network topology exhibits a power-law degree distribution: P(k) ~k − γ , where k is the number of link attached to a randomly chosen node in the network and γ is the scaling exponent. SFN is named for the fact that the power-law distributions do not have a median thad implies a typical size of the system[6]. It is also known that the average path length between the nodes are surprisingly small in SFN[7], hence the efficient transport is expected over the network.

This paper introduces the multi-locomotion robot which has multiple types of locomotion at first. The robot has been developed to achieve a bipedal walk, a quadrupedal walk, and a brachiation, mimicking locomotion ways of a gorilla. It therefore has higher mobility by selecting a proper locomotion type according to its environment and purpose. When we consider a transition motion connecting one locomotion form to another, two designed controllers corresponding to each locomotion type are not enough. A new control algorithm that covering control properties of two locomotion controllers should be developed, because the intermediate motion cannot be realized by fusing control outputs from two controllers. Previously, based on this notion, we have proposed a novel method named Passive Dynamic Autonomous Control (PDAC) that realized not only a bipedal walk but also a quadruped walk. In this paper, the PDAC is also applied to a brachiation motion on the irregular ladder; then the proposed controller is validated by the experiment.

Automatic detection and description of events, particularly human behavior, is one of the most challenging issues, since event interpretation is highly dependent on the target of attention, which is not uniquely specified. In order to tackle this problem, we propose the concept of a “Cognitive Ontology” as a framework for a system that can automatically decide the attention focus and describe the events. A cognitive ontology is structured with conceptual units which are Entities and Relations, and these units enable robot endogenous attention fixation and jumps based on a networked Cognitive Ontology. In addition, we introduce exogenous attention fixation based on how the observed targets differ from a predicted pattern. In this process, the corresponding target of attention is updated and assigned to an event description buffer that consists of two Entities and one Relation. In this paper, we have developed and experimented with this holistic event interpretation process taking into account endogenous attention, exogenous attention and determined event description.

The issue on optimality and robustness has become a major concern in large-scale network systems. While a star-like centralized network surtcture is optimal in terms of the average path length, it is vulnerable to the breakdown arising in the central node. Scale-free network (SFN) is known to be effective topology in terms of both the average path length and robustness against random breakdown. However, if the hub nodes are intentionally attacked, SFN is found vulnerable. In this paper, we propose an evolutionary network model which reconfigures a network suructure according to the various types of breakdown or intentional attacks while maintaining the system performance. The local evaluation indice and control parameters are introduced to regulate a balance between efficiency and robustness. Simulation results suggest that the proposed approach is promising.

This paper describes a novel distributed communication timing control for wireless sensor networks. For collision avoidance among sensor nodes, communication slots are allocated with a centralized controller in TDMA, however, we propose Phase Diffusion Synch-Alliance model as a fully distributed communication timing control. This model is based on the coupled phase-oscillator dynamics to dynamically adjust communication timing where phase synchronization and repulsion are coordinated depending on the network topology.