Disaster robots have accepted tele-operation in order to share the intelligence of human operators and robot systems. Virtual wall is one of the tele-operation technology to support recognition of human operator. If the virtual wall can block the robot from dangers, the operator will feel comfortable and can concentrate on fundamental missions. In this paper, we proposes and compares three methods for virtual wall visualization in tele-operation using 3D reconstruction. First is a virtual wall visualized only with edges. A wall filled with transparent color is the second method. Finally, third method is a texture-mapped virtual wall. In the experiments, we discuss their merits and demerits in view of robot tele-operation.

Navigating an unknown environment is a challenging task for a robot, especially when a large number of obstacles exist and the odometry lacks reliability. Pose tracking allows the robot to determine its location relative to its previous location. The ICP (iterative closest point) has been a powerful method for matching two point clouds and determining the transformation matrix between the maps. However, in a situation where odometry is not available and the robot moves far from its original location, the ICP fails to calculate the exact displacement. In this paper, we suggest a method that is able to match two different point clouds taken a long distance apart. Without using any odometry information, it only exploits the features of corner points containing information on the surroundings. The algorithm is fast enough to run in real time.

This paper presents the kinematic and dynamic analysis of the robot arm for inspection and rescue operations. The inspection robot arm has Pitch-Pitch-Pitch-Yaw motion for an optimal and stable view of the camera installed at the end of the manipulator. The rescue operation robot arm has Yaw-Pitch-Pitch-Roll motion to handle heavy tools. Additionally, both robot arms are waterproof, as they use the triple-layer O-ring. Furthermore, the dynamic equation including the damping force due to the mechanical seal for waterproofness was derived by using the Newton-Euler method. A control system using the ARM processor was developed and introduced in this paper, and its performance was verified through experiments.

In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

This paper presents a novel driving system by the humanoid robot to drive a vehicle in disaster response situations. To enhance robot's capability for substituting human activities in responding to natural and man-made disaster, the one of prerequisite skills for the rescue robot is the mounted mobility to maneuver a vehicle safely in disaster site. Therefore, our driving system for the humanoid is developed in order to steer a vehicle through unknown obstacles even under poor communication conditions such as time-delay and black-out. Especially, the proposed system includes a tele-manipulation interface and stable navigation strategies. First, we propose a new type of path estimation method to overcome limited communication. Second, we establish navigation strategies when the operator cannot recognize obstacles based on Dynamic Window Approach. The effectiveness of the proposed developments is verified through simulation and experiments, which demonstrate suitable system for driving a vehicle in disaster response.

This paper presents various strategies for humanoid vehicle driving and egress tasks. For driving, a tele-operating system that controls a robot based on a human operator's commands is built. In addition, an autonomous assistant module is developed for the operator. Normal position control can result in severe damage to robots when they egress from vehicles. To prevent this problem, another approach that mixes various joint control techniques is adopted in this study. Additionally, a footplate is newly designed and attached to the vehicle floor for the ground landing phase of the egress task. The attached plate enables the robot to step down onto the ground in a safe manner. For stable locomotion, a balance controller is designed for the humanoid. For the design of the controller, the robot is modeled using an inverted pendulum that consists of a spring and a damper. Then, a state feedback controller (with pole placement and a state observer) is built based on the simplified model. Many approaches that are presented in this paper were successfully applied to a full-sized humanoid, DRC-HUBO+, in the DARPA Robotics Challenge Finals, which were held in the United States in 2015.

This paper proposes a robust control design method for improving the cornering stability of a personal electric vehicle equipped with in-wheel motors. In general, vehicles undergo severe parameter variations and unpredictable disturbances with respect to a wide range of driving conditions (e.g., road surface conditions and vehicle velocity conditions). For this reason, robust control design techniques are required to guarantee consistent driving performances and robustness against various driving conditions. In this paper, an adaptive sliding mode control method is employed to enhance cornering stability by controlling the direct-drive in-wheel motors independently. Additionally, in order to confirm the effectiveness of a proposed control method, real driving tests with an experimental personal electric vehicle are performed.

The BLDC motor is used widely in industry due to its controllability and freedom from maintenance because there is no mechanical brush in the BLDC motor. Furthermore, it is suitable for high-speed applications, such as compressors and air blowers. For instance, for a compressor with a small impeller due to miniaturizing, the BLDC motor has to rotate at a very high speed to maintain the compression ratio of the compressor. Typically, to reach an ultra-high speed, airfoil bearings must be used in place of ball bearings because of their friction. Unfortunately, the characteristics of airfoil bearings change drastically depending on the revolution speed. In this paper, a BLDC motor with airfoil bearings is controlled with a PID controller. To analyze and determine the PID coefficients, the relay-feedback method is used. Additionally, for adaptive control, a fuzzy logic controller is used. Furthermore, the auto-tuning and self-tuning techniques are combined to control the BLDC motor. The proposed method is able to control the airfoil-bearing BLDC motor efficiently.

In this paper, we present a method for the inspection of diamond wheels. In total, six items, including height, radius, and angle, need to be checked during the manufacturing of a diamond wheel. Automatic inspection through image processing is presented in this paper. First, a contour corresponding to the boundary of the diamond wheel is extracted from an image. Next, control points are selected by processing the contour. Seven control points are detected and used for the computation of the required item. Detailed procedures for the computation of the height, radius, and angle using control points are presented in this paper. Experimental results show the feasibility of the presented method.

Vertical velocity is critical in many areas, such as the control of unmanned aerial vehicles, fall detection, and virtual reality. Conventionally, the integration of GPS (Global Positioning System) with an IMU (Inertial Measurement Unit) was popular for the estimation of vertical components. However, GPS cannot work well indoors and, more importantly, has low accuracy in the vertical direction. In order to overcome these issues, IMU-barometer integration has been suggested instead of IMU-GPS integration. This paper proposes a new complementary filter for the estimation of vertical velocity based on IMU-barometer integration. The proposed complementary filter is designed to minimize drift error in the estimated velocity by adding PID control in addition to a zero velocity update technique.

Resistance temperature detectors (RTDs) and thermocouple sensors are broadly used to measure temperatures in the engineering and research fields. The contents of this standard calibration procedure (SCP) describe procedures related to the calculation of an electrical temperature calibrator and show different ways to indicate the calibration results, such as measurement uncertainty. As an SCP for the electrical temperature calibrator has not been developed yet, we studied the SCP and found a solution to this problem. In this paper, we present a mathematical model of the data and measurement variations with the calibration data results.

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

This paper proposes a new concept of a soft and wearable upper-limb exoskeleton. A novel actuation principle, called the twisted string actuation principle, is implemented to make it lightweight, soft, and therefore easily wearable. Its power transmission mechanism and harness are designed to be soft and wearable, yet have enough control accuracy for rehabilitation. In addition to force transmission optimization, a speed enlargement mechanism is newly introduced in order to increase the contraction speed of the twisted string actuation mechanism by sacrificing the unnecessarily large gear reduction ratio of the twisted string mechanism. A prototype has been tested for mirroring therapy, and the feasibility of the proposed mechanism has been shown through a sufficiently accurate tracking performance.

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.

This paper proposes a novel code-tracking scheme to track the fine code synchronization for BOC (pn,n)-modulated global navigation satellite system signals in a repeat-back jamming environment. The correlation function of BOC (pn,n)-modulated signals has several peaks. The correlation function in the advanced offset region remains almost unchanged due to the repeat-back signals being received later than a line-of-sight signal in the same multipath signal receiving case. Additionally, the combined pseudo-random noise signal can be treated as repeat-back jamming signals, like multipath signals. In this paper, we propose a novel code-tracking scheme utilizing the advantages of using a combined pseudo-random noise signal in the advanced offset region and verify its performance through simulation.

In wireless mesh sensor networks (WMSNs), sensor nodes are connected in the form of a mesh topology and transfer sensor data by multi-hop routing. A data aggregation method for WMSNs is required to minimize the number of routing hops and the energy consumption of each node with limited battery power. This paper presents a shortest path data aggregation method for WMSNs. The proposed method utilizes a simple hash function based on shuffled row major indexing for addressing sensor nodes. This allows sensor data to be aggregated without complex routing tables and calculation for deciding the next hop. The proposed data aggregation algorithms work in a fractal fashion with different mesh sizes. The method repeatedly performs gathering and moves sensor data to sink nodes in higher-level clusters. The proposed method was implemented and simulations were performed to confirm the accuracy of the proposed algorithms.