Certain open issues challenge the software engineering of autonomous robot software (ARS). One issue is to provide enabling software technologies to support autonomous and rational behaviours of robots operating in an open environment, and another issue is the development of an effective engineering approach to manage the complexity of ARS to simplify the development, deployment and evolution of ARS. We introduce the software framework AutoRobot to address these issues. This software provides abstraction and a model of accompanying behaviours to formulate the behaviour patterns of autonomous robots and enrich the coherence between task behaviours and observation behaviours, thereby improving the capabilities of obtaining and using the feedback regarding the changes. A dual-loop control model is presented to support flexible interactions among the control activities to support continuous adjustments of the robot's behaviours. A multi-agent software architecture is proposed to encapsulate the fundamental software components. Unlike most existing research, in AutoRobot, the ARS is designed as a multi-agent system in which the software agents interact and cooperate with each other to accomplish the robot's task. AutoRobot provides reusable software packages to support the development of ARS and infrastructure integrated with ROS to support the decentralized deployment and running of ARS. We develop an ARS sample to illustrate how to use the framework and validate its effectiveness.

A component-oriented FPGA design platform is proposed for robot system integration. FPGAs are known to be a power-efficient hardware platform, but the development cost of FPGA-based systems is currently too high to integrate them into robot systems. To solve this problem, we propose an FPGA component that allows FPGA devices to be easily integrated into robot systems based on the Robot Operating System (ROS). ROS-compliant FPGA components offer a seamless interface between the FPGA hardware and software running on the CPU. Two experiments were conducted using the proposed components. For the first experiment, the results show that the execution time of an FPGA component for image processing was 1.7 times faster than that of the original software-based component and was 2.51 times more power efficient than an ordinary PC processor, despite substantial communication overhead. The second experiment showed that an FPGA component for sensor fusion was able to process multiple sensor inputs efficiently and with very low latency via parallel processing.

In this letter, we investigate the computation offloading problem in cloud based multi-robot systems, in which user weights, communication interference and cloud resource limitation are jointly considered. To minimize the system cost, two offloading selection and resource allocation algorithms are proposed. Numerical results show that the proposed algorithms both can greatly reduce the overall system cost, and the greedy selection based algorithm even achieves near-optimal performance.

Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. The problem is, high overall system costs are the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyzes a nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments. The aim of this research is to improve efficiency of mechanisms for reducing the cost by developing a new algorithm for the synergistic cooperation of the group. In this paper, we set the evaluation index of energy efficiency considering that the mission success rate as well as energy saving is important. The value is calculated as the number of successful operations against the total consumption of energy in order to also guarantee optimized for the work processing power than the one simple goal of energy savings. The method employs a behavioral model of a honey bee swarm to improve the energy efficiency in collecting crops or minerals. Experiments demonstrate the effectiveness of the approach. The experiment is set a number of strategies to combine the techniques to the proposed and conventional methods. Considering variables such as the area of search space and the size of a swarm, the efficiency comparison test is performed. As the result, the proposed method showed the enhanced energy efficiency of the average 76.9% as compared to the conventional simple model that means reduction of the recharging cost more than 40%.

This paper proposed patient friendly capsule endoscopy (CE) for not only screening but also treatment. Two different types of CEs with an Internet utility were investigated. The first type used magnetic navigation in the stomach and colon for screening. Magnetic navigation enabled the capsule to explore the whole of the gastrointestinal tract with less risk of missing lesions and complete the screening within the battery life. The system's design was patiently friendly as it allowed the subjects to leave the hospital after the capsule had been navigated in the stomach. The second investigated two different therapeutic robotic endoscopes. Both prototypes were driven by DC motors and controlled remotely via the internet. In addition, they were equipped with therapeutic tools and each prototype's ability with the tools was assessed. The investigation showed it was possible to remotely control both prototypes and operate therapeutic tools via the Internet. The investigation identified areas for improvement, such as size, connection speed, security of data, and the holding the capsule's position during treatment, In conclusion, both methods have the potential to make capsule endoscopy a very patient friendly procedure that can be carried out anywhere.

Sound source localization (SSL), with a binaural input in practical environments, is a challenging task due to the effects of noise and reverberation. In psychoacoustic research field, one of the theories to explain the mechanism of human perception in such environments is the well-known equalization-cancellation (EC) model. Motivated by the EC theory, this paper investigates a binaural SSL method by integrating EC procedures into a beamforming technique. The principle idea is that the EC procedures are first utilized to eliminate the sound signal component at each candidate direction respectively; direction of sound source is then determined as the direction at which the residual energy is minimal. The EC procedures applied in the proposed method differ from those in traditional EC models, in which the interference signals in rooms are accounted in E and C operations based on limited prior known information. Experimental results demonstrate that our proposed method outperforms the traditional SSL algorithms in the presence of noise and reverberation simultaneously.

This paper presents an experimental study that analyzes how conversational agents activate human communication in thought-evoking multi-party dialogues between multi-users and multi-agents. A thought-evoking dialogue is a kind of interaction in which agents act to provoke user thinking, and it has the potential to activate multi-party interactions. This paper focuses on quiz-style multi-party dialogues between two users and two agents as an example of thought-evoking multi-party dialogues. The experimental results revealed that the presence of a peer agent significantly improved user satisfaction and increased the number of user utterances in quiz-style multi-party dialogues. We also found that agents' empathic expressions significantly improved user satisfaction, improved user ratings of the peer agent, and increased the number of user utterances. Our findings should be useful for activating multi-party communications in various applications such as pedagogical agents and community facilitators.

In this paper we present a cognitive architecture inspired on the biological functioning of the motor system in humans. To test the model, we built a robotic hand with a Lego Mindstorms™ kit. Then, through communication between the architecture and the robotic hand, the latter was able to perform the movement of the fingers, which therefore allowed it to perform grasping of some objects. In order to obtain these results, the architecture performed a conversion of the activation of motor neuron pools into specific degrees of servo motor movement. In this case, servo motors acted as muscles, and degrees of movement as exerted muscle force. Finally, this architecture will be integrated with high-order cognitive functions towards getting automatic motor commands generation, through planning and decision making mechanisms.

Although many companies have developed robots that assist humans in the activities of daily living, safety requirements and test methods for such robots have not been established. Given the risk associated with a robot malfunctioning in the human living space, from the viewpoints of safety and EMC, it is necessary that the robot does not create a hazardous situation even when exposed to possibly severe electromagnetic disturbances in the operating environment. Thus, in immunity tests for personal care robots, the safety functions should be more rigorously tested than the other functions, and be repeatedly activated in order to ascertain that the safety functions are not lost in the presence of electromagnetic disturbances. In this paper, immunity test procedures for personal care robots are proposed that take into account functional safety requirements. A variety of test apparatuses are presented, which were built for activating the safety functions of robots, and detecting whether they were in a safe state. The practicality of the developed immunity test system is demonstrated using actual robots.

This paper introduces a comparison of three automatic gait generation methods for quadruped robots: GA (Genetic Algorithm), GP (genetic programming) and CPG (Central Pattern Generator). It aims to provide a useful guideline for the selection of gait generation methods. GA-based approaches seek to optimize paw locus in Cartesian space. GP-based techniques generate joint trajectories using regression polynomials. The CPGs are neural circuits that generate oscillatory output from an input coming from the brain. Optimizations for the three proposed methods are executed and analyzed using a Webots simulation of the quadruped robot built by Bioloid. The experimental comparisons and analyses provided herein will be an informative guidance for research of gait generation method.

Robot covering problem has gained attention as having the most promising applications in our real life. Previous spanning tree coverage algorithm addressed this problem well in a static environment, but not in a dynamic one. In this paper, we present and analyze our algorithm workable in a dynamic environment with less shadow areas.

We propose a motor speed ripple elimination method using a state dependent disturbance observer (SDDOB). The SDDOB eliminates the state dependent disturbance in the system regardless of the operation frequency, input time delay and output time delay. The SDDOB and a main proportional integral (PI) controller constitute a robust motor speed controller. Experimental results show the effectiveness of the proposed method.

The gathering problem of anonymous and oblivious mobile robots is one of the fundamental problems in the theoretical mobile robotics. We consider the gathering problem in unoriented and anonymous rings, which requires that all robots eventually keep their positions at a common non-predefined node. Since the gathering problem cannot be solved without any additional capability to robots, all the previous results assume some capability of robots, such as the agreement of local view. In this paper, we focus on the multiplicity detection capability. This paper presents a deterministic gathering algorithm with local-weak multiplicity detection, which provides a robot with information about whether its current node has more than one robot or not. This assumption is strictly weaker than that in previous works. Our algorithm achieves the gathering from an aperiodic and asymmetric configuration with 2 < k < n/2 robots, where n is the number of nodes. We also show that our algorithm is asymptotically time-optimal one, i.e., the time complexity of our algorithm is O(n). Interestingly, despite the weaker assumption, it achieves significant improvement compared to the previous algorithm, which takes O(kn) time for k robots.

This paper describes an overview of demands on wireless communications from the point of view of robotics, oceanics and aviation technologies. These technologies are mostly applied to extreme environments, where humans cannot easily approach and directly operate equipment. In such environments, reliable and robust wireless communications are highly required to perform missions perfectly. However, there are many issues for wireless technologies to meet those requirements due to poor propagation and large delay conditions. This paper discusses wireless communication technologies required in land-sea-and-air environments based on the recent development challenges of unmanned ground and marine robots and next-generation air-transportation systems. This paper will contribute future wireless communication techniques for unmanned robots and next-generation aviations.

In this paper, we consider a problem of simultaneously optimizing a sequence of graphs and a route which exhaustively visits the vertices from each pair of successive graphs in the sequence. This type of problem arises from repetitive routing of grasp-and-delivery robots used in the production of printed circuit boards. The problem is formulated as follows. We are given a metric graph G*=(V*,E*), a set of m+1 disjoint subsets Ci ⊆ V* of vertices with |Ci|=n, i=0,1,...,m, and a starting vertex s ∈ C0. We seek to find a sequence π=(Ci1, Ci2, ..., Cim) of the subsets of vertices and a shortest walk P which visits all (m+1)n vertices in G* in such a way that after starting from s, the walk alternately visits the vertices in Cik-1 and Cik, for k=1,2,...,m (i0=0). Thus, P is a walk with m(2n-1) edges obtained by concatenating m alternating Hamiltonian paths between Cik-1 and Cik, k=1,2,...,m. In this paper, we show that an approximate sequence of subsets of vertices and an approximate walk with at most three times the optimal route length can be found in polynomial time.

Although there have been enormous investments into English education all around the world, not many differences have been made to change the English instruction style. Considering the shortcomings for the current teaching-learning methodology, we have been investigating advanced computer-assisted language learning (CALL) systems. This paper aims at summarizing a set of POSTECH approaches including theories, technologies, systems, and field studies and providing relevant pointers. On top of the state-of-the-art technologies of spoken dialog system, a variety of adaptations have been applied to overcome some problems caused by numerous errors and variations naturally produced by non-native speakers. Furthermore, a number of methods have been developed for generating educational feedback that help learners develop to be proficient. Integrating these efforts resulted in intelligent educational robots – Mero and Engkey – and virtual 3D language learning games, Pomy. To verify the effects of our approaches on students' communicative abilities, we have conducted a field study at an elementary school in Korea. The results showed that our CALL approaches can be enjoyable and fruitful activities for students. Although the results of this study bring us a step closer to understanding computer-based education, more studies are needed to consolidate the findings.

Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in recent mobile robotics. This “map compression” problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is the proposal of the dictionary-based map compression approach. A map compression system is presented by employing RANSAC map matching and sparse coding as building blocks. The effectiveness levels of the proposed techniques is investigated in terms of map compression ratio, compression speed, the retrieval performance of compressed/decompressed maps, as well as applications to the Kolmogorov complexity.

In this paper, we propose a method for robot self-position identification by active sound localization. This method can be used for autonomous security robots working in room environments. A system using an AIBO robot equipped with two microphones and a wireless network is constructed and used for position identification experiments. Differences in arrival time to the robot's microphones are used as localization cues. To overcome the ambiguity of front-back confusion, a three-head-position measurement method is proposed. The position of robot can be identified by the intersection of circles restricted using the azimuth differences among different sound beacon pairs. By localizing three or four loudspeakers as sound beacons positioned at known locations, the robot can identify its position with an average error of 7 cm in a 2.53.0 m2 working space in the horizontal plane. We propose adjusting the arrival time differences (ATDs) to reduce the errors caused when the sound beacons are high mounted. A robot navigation experiment was conducted to demonstrate the effectiveness of the proposed position-identification system.

A min-max model predictive controller is developed in this paper for tracking control of wheeled mobile robots (WMRs) subject to the violation of nonholonomic constraints in an environment without obstacles. The problem is simplified by neglecting the vehicle dynamics and considering only the steering system. The linearized tracking-error kinematic model with the presence of uncertain disturbances is formed in the frame of the robot. And then, the control policy is derived from the worst-case optimization of a quadratic cost function, which penalizes the tracking error and control variables in each sampling time over a finite horizon. As a result, the input sequence must be feasible for all possible disturbance realizations. The performance of the control algorithm is verified via the computer simulations with a predefined trajectory and is compared to a common discrete-time sliding mode control law. The result shows that the proposed method has a better tracking performance and convergence.

In this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.