With technical advances, various locomotion mechanisms for use on bumpy roads have been introduced. Among these locomotion mechanisms, crawler-based platforms are widely employed. However, due to their tilt on uneven terrain, accidents such as overturning and falling loads have been reported. To overcome these situations, this paper proposes a constant balance scheme for crawler-based transportation systems (hereinafter called crawler robots for simplicity). Practically, a variable-shape crawler robot with four foldable legs is designed to maintain a constant upper-frame posture regardless of ground conditions. The four legs by coordinating expand and contract, thereby enabling the robot to adapt to local surface conditions and configure its desired posture while traveling. The coordination-based crawler mechanism is realized by employing rack-and-pinion units for raising and lowering. The effectiveness and performance of the developed crawler robot are demonstrated by verifying its movement under continuous and discontinuous surface conditions with the use of a balanced posture from a tilted state. Specifically, we pose an innovative challenge of information transformation to maintain balance effectively. In detail, three-dimensional state variations (e.g., gradients and inclinations) of the crawler robot depending on ground conditions are transformed into one-dimensional displacements. Unlike previous works, this study presents the novel idea of coordinating the motions of individual legs to configure a variable-shape crawler robot. In other words, the crawler shape is deformed while it maintains the desired balance.

This paper presents an interactive control for our assistive robotic walker, the JAIST Active Robotic Walker (JARoW), developed for elderly people in need of walking assistance. The focus of our paper is placed on how to estimate the user's walking parameters by sensing the locations of lower limbs and to predict his or her walking patterns. For this purpose, a particle-filter-based prediction technique and a motion controller are developed to help JARoW smoothly generate the direction and velocity of its movements in a way that reflects the prediction. The proposed scheme and its implementation are described in detail, and outdoor experiments are performed to demonstrate its effectiveness and feasibility in everyday environments.

This paper presents a novel interactive control for our assistive robotic walker, the JAIST Active Robotic Walker (JARoW), developed for elderly people in need of assistance. The aim of our research is to recognize characteristics of the user's gait and to generate the movement of JARoW accordingly. Specifically, the proposed control enables JARoW to accurately generate the direction and velocity of its movement in a way that corresponds to the user's variable walking behaviors. The algorithm and implementation of the control are explained in detail, and the effectiveness and usability of JARoW are verified through extensive experiments in everyday environments.

This paper proposes a new attention-path planning algorithm that allows robots with limited sensing coverage to identify an unknown entity efficiently. Our focus is placed on how to plan optimal sequences of views to access more useful information needed to understand the entity. The adaptive submodular optimization technique guaranteed to achieve near-optimal performance is used to maximize the expected information gain. We verified the validity of the proposed approach to the face recognition problem through preliminary experiments.

In this paper, we describe the design and implementation of an integrated two dimensional and three dimensional location measurement system, where different types of range sensors can be mounted onto the spiral motion positioner. The proposed sensor/positioner system enables terrestrial and aerial robots to observe their surroundings in all directions without blind spots. Using a nut-and-bolt and link mechanism, the proposed positioner driven by a single stepper motor exhibits continuous three dimensional spiral trajectories over the upper hemisphere. This single axis motor driven system helps decrease the size, weight, and structural complexity of the system. Particular attention in this work is placed on how to effectively combine two dimensional and three dimensional measurement functions. We verify the validity and effectiveness of the proposed location measurement system through simulations and experiments. It is expected that the proposed system can be incorporated into a wide range of mobile robot platforms.

This paper presents a new control scheme of an assistive robotic cart that helps a user easily transport objects in various weights. The maneuverability of the cart would be highly affected by the loaded weight of the cart and the friction between the wheel and the floor. Our focus is placed on how to enable the cart to offer easy maneuverability by creating desired interactions with a user. For this, a switched observer based impedance control scheme is proposed to allow the cart to autonomously adapt to changes in the weight of the load and the friction. Specifically, a pre-determined impedance between the user and the cart is regulated to generate an assist force using the user's input force and the velocity of the cart. The switched observer is designed to estimate the loaded weight and the friction coefficient for the precise computation of the amount of assistance. Further, using the process integration and design optimization approach, the observer gains are automatically adjusted, resulting in enhancing the control performance. We describe the proposed scheme in detail, and perform extensive simulations to demonstrate its effectiveness.

This paper presents a new control scheme of JAIST Active Robotic Walker (JARoW) developed to provide elderly people with sufficient ambulatory capability. Toward its practical use, our focus is placed on how to allow easier and reliable maneuverability by creating a natural user interface. Specifically, our challenge lies in providing a well-functioning controller by detecting what the user wants to do or their intentions. A Kalman filter based tracking scheme is realized to estimate and predict the locations of the user's legs and body in real time. The feedback control can then adjust the motions of JARoW corresponding to the actual user's walking behaviors. Our experiments confirm that JARoW can autonomously adjust its motion direction and velocity without requiring any additional control inputs.

We present a new control scheme of JAIST Active Robotic Walker (JARoW) developed to provide potential users such as the elderly with sufficient ambulatory capability. Toward its practical use, we tackle JARoW's easy and reliable maneuverability by creating a natural user interface between a user and JARoW. Specifically, our focus is placed on how to realize the natural and smooth movement of JARoW despite different gait parameters of users. For this purpose, a particle filtered interface function (PFIF) is proposed to estimate and predict the locations of the user's legs and body. Then, the simple feedback motion control function adjusts the motions of JARoW corresponding to the estimation and prediction. Experimental results show that the proposed control scheme can be quite satisfactory for practical use without requiring any additional user effort.

This paper presents a novel low-cost position detection prototype from practical design to implementation of its control schemes. This prototype is designed to provide mobile robot swarms with advanced sensing capabilities in an efficient, cost-effective way. From the observation of bats' foraging behaviors, the prototype with a particular emphasis on variable rotation range and speed, as well as 360° observation capability has been developed. The prototype also aims at giving each robot reliable information about identification of neighboring robots from objects and their positions. For this purpose, an observation algorithm-based sensor is proposed. The implementation details are explained, and the effectiveness of the control schemes is verified through extensive experiments. The sensor provides real-time location of stationary targets positioned 100 cm away within an average error of 2.6 cm. Moreover, experimental results show that the prototype observation capability can be quite satisfactory for practical use of mobile robot swarms.

This paper addresses the deployment problem for a swarm of autonomous mobile robots initially randomly distributed in 3 dimensional space. A fully decentralized geometric self-configuration approach is proposed to deploy individual robots at a given spatial density. Specifically, each robot interacts with three neighboring robots in a selective and dynamic fashion without using any explicit communication so that four robots eventually form a regular tetrahedron. Using such local interactions, the proposed algorithms enable a swarm of robots to span a network of regular tetrahedrons in a designated space. The convergence of the algorithms is theoretically proved using Lyapunov theory. Through extensive simulations, we validate the effectiveness and scalability of the proposed algorithms.

We address the problem of dispersing a large number of autonomous mobile robots toward building wireless ad hoc sensor networks performing environmental monitoring and control. For the purpose, we propose the adaptive triangular mesh generation algorithm that enables robots to generate triangular meshes of various sizes adapting to changing environmental conditions. A locally interacting, geometric technique allows robots to generate each triangular mesh with their two neighbor robots. Specifically, we have assumed that robots are not allowed to have the identifier, any pre-determined leaders or common coordinate systems, and any explicit communication. Under such minimal conditions, the positions of the robots were shown to converge to the desired distribution, which was mathematically proven and also verified through extensive simulations. Our preliminary results indicate that the proposed algorithm can be applied to the problem regarding the coverage of an area of interest by a swarm of mobile sensors.

This paper presents practical design and hardware implementation issues of self-configuring swarms of autonomous mobile robots. For the purpose, we develop a new low-cost position detection system that we call dual rotating infrared (DRIr) sensor. The DRIr sensor can provide robots with advanced sensing capabilities that give reliable information about the position and surface geometry of neighboring robots and obstacles. Special focus is placed on how to realize the observation and object identification of mobile robots through the use of DRIr sensors. We verify the functionality and performance of the DRIr sensors mounted on a commercial mobile robot. Experimental results show that a swarm of mobile robots equipped with the DRIr sensors can autonomously configure themselves into an area.

We address the problem of deploying a swarm of autonomous mobile robots toward building an ad hoc network of robotic sensors with spatial uniform density. For the purpose, each of the robots configures themselves into an area with geographical constraints through local interactions with two adjacent neighboring robots. The basic idea underlying this work is that robots can be thought of as liquid particles that change their positions conforming to the shape of the container they occupy. The main challenge is how to cope with the accuracy limitations of sensors and possible holes in the configuration. Considering such realistic conditions, the convergence of the proposed method is proved using Lyapunov’s theorem. The proposed method is verified to be effective through the simulation for the secure deployments of robotic sensor network.

This paper presents a motion planning framework for a large number of autonomous robots that enables the robots to configure themselves adaptively into an area of an arbitrary geometry. A locally interacting geometric technique provides a unique solution that allows the robots to converge to the uniform distribution by forming an equilateral triangle with their two neighbors. The basic idea underlying the proposed solution is that robots can be thought of as liquid particles that change their relative positions conforming to the shape of the container they occupy. Specifically, it is assumed that robots are not allowed to have the identification number, a pre-determined leader, a common coordinate system, and communication capabilities. Under such minimal conditions, the convergence of the algorithm is mathematically proved and verified through extensive simulations. The results validate the feasibility of applying the algorithm to self-configuration of mobile sensors across the constrained environment.

In this study, we focus on a self-deployment problem for a swarm of autonomous mobile robots that can be used to build a sensor networking infrastructure with equilateral triangle lattice configurations. In order to deploy the swarm, this paper proposes a self-stabilizing distributed self- deployment algorithm under a robot model with the following features: no identification numbers, no common coordinates, no predetermined leader, no memory for past actions and implicit communication. Regardless of the restricted model, our proposed algorithm based on local interactions provides a solution for the self-deployment problem. Moreover, the algorithm provides robust capability of swarm connectivity in spite of loss of several robots. We discuss in details the features of the algorithm, including self-organization, self-stabilization, and robustness. A simulation study demonstrates the validity of the algorithm.

This paper presents a novel flocking strategy for a large-scale swarm of robots that enables the robots to navigate autonomously in an environment populated with obstacles. Robot swarms are often required to move toward a goal while adapting to changes in environmental conditions in many applications. Based on the observation of the swimming behavior of a school of tunas, we apply their unique patterns of behavior to the autonomous adaptation of the shape of robot swarms. Specifically, each robot dynamically selects two neighboring robots within its sensing range and maintains a uniform distance with them. This enables three neighboring robots to form a regular triangle and remain stable in the presence of obstacles. Therefore, the swarm can be split into multiple groups or re-united into one according to environmental conditions. More specifically, assuming that robots are not allowed to have individual identification numbers, a pre-determined leader, memories of previous perceptions and actions, and direct communications to each other, we verify the validity of the proposed algorithm using the in-house simulator. The results show that a swarm of robots repeats the process of partition and maintenance passing through multiple narrow passageways

Diseases in the gastro-intestinal tract are on an increasing trend. In order to diagnose a patient, various signals of the digestive organ, such as temperature, pH, and pressure, can offer the helpful information. Among the above mentioned signals, we choose the pressure variation as a monitoring signal. The variation of a pressure signal of the gastro-intestinal tract can offer the information of a digestive trouble or some clues of the diseases. In this paper, a pressure monitoring system for the digestive organs of a living pig is presented. This is why a pig’s gastro-intestinal tract is very similar as human’s. This system concept is to transmit the measured biomedical signals from a transmitter in a living pig to a wireless receiver that is positioned out of body. The integrated solution includes the following parts: (1) the swallow type pressure capsule, (2) the receiving set consisting of a receiver, decoder box, and PC. The merit of the proposed system is that the monitoring system can supply the precise and repeatable pressure in the gastro-intestinal tract. In addition, the design of low power consumption enables it to keep sending reliable signals while the pressure capsule is working in the digestive organ. The subject of the study for the pressure monitoring system is in-vivo experiments for a living pig. We achieved the pressure tracings in digestive organs and verified the validity of system after several in-vivo tests using the pressure monitoring system.