Perception as a key component for cognitive technical systems

Cognitive capabilities such as perception, reasoning, learning, and planning turn technical systems into systems that “know what they are doing.” Starting from the human brain the Cluster of Excellence “CoTeSys” investigates cognition for technical systems such as vehicles, robots, and factories. Technical systems that are cognitive will be much easier to interact and cooperate with, and will be more robust, flexible, and efficient. For understanding their environment and interacting with humans the cognitive system’s most important sense is the visual one. The talk presents recent results using the visual sensor in building environment models, self localization of autonomous moving robots, navigation, simultaneous tracking of groups of humans and robots, face detection and evaluation of gaze direction and facial expression, and emotional communication between humans and robots.     

A Real-Time Hybrid Architecture for Biped Humanoids with Active Vision Mechanisms

A real-time hybrid control architecture for biped humanoid robots is proposed. The architecture is modular and hierarchical. The main robot’s functionalities are organized in four parallel modules: perception, actuation, world-modeling, and hybrid control. Hybrid control is divided in three behavior-based hierarchical layers: the planning layer, the deliberative layer, and the reactive layer, which work in parallel and have very different response speeds and planning capabilities. The architecture allows: (1) the coordination of multiple robots and the execution of group behaviors without disturbing the robot’s reactivity and responsivity, which is very relevant for biped humanoid robots whose gait control requires real-time processing. (2) The straightforward management of the robot’s resources using resource multiplexers. (3) The integration of active vision mechanisms in the reactive layer under control of behavior-dependant value functions from the deliberative layer. This adds flexibility in the implementation of complex functionalities, such as the ones required for playing soccer in robot teams. The architecture is validated using simulated and real Nao humanoid robots. Passive and active behaviors are tested in simulated and real robot soccer setups. In addition, the ability to execute group behaviors in real- time is tested in international robot soccer competitions.     

Adaptation and user expertise modelling in AthosMail

This article describes the User Model component of AthosMail, a speech-based interactive e-mail application developed in the context of the EU project DUMAS. The focus is on the system’s adaptive capabilities and user expertise modelling, exemplified through the User Model parameters dealing with initiative and explicitness of the system responses. The purpose of the conducted research was to investigate how the users could interact with a system in a more natural way, and the two aspects that mainly influence the system’s interaction capabilities, and thus the naturalness of the dialogue as a whole, are considered to be the dialogue control and the amount of information provided to the user. The User Model produces recommendations of the system’s appropriate reaction depending on the user’s observed competence level, monitored and computed on the basis of the user’s interaction with the system. The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.The research was done while the author was affiliated with the University of Art and Design Helsinki as the scientific coordinator of the DUMAS project.     

环境因素对多自主移动机器人系统的影响研究

基于行为的多自主移动机器人所处的环境因素总是对其系统性能造成一定的影响。本文针对典型的群体觅食任务,以计算机仿真为手段,研究目标物数量、障碍物数量、搜索区域大小和机器人数目对其系统性能的影响。仿真实验结果表明搜索区域内的目标物数量越多,障碍物数量越少,系统性能越高;而搜索区域大小和机器人数目增加到某一定值时,系统性能开始下降。     

Development of distance recognition using an ocellus camera for an autonomous personal robot

We are attempting to develop an autonomous personal robot that has the ability to perform practical tasks in a human living environment by using information derived from sensors. When a robot operates in a human environment, the issue of safety must be considered in regard to its autonomous movement. Thus, robots absolutely require systems that can recognize the external world and perform correct driving control. We have thus developed a navigation system for an autonomous robot. The system requires only image data captured by an ocellus CCD camera. In this system, we allow the robot to search for obstacles present on the floor. Then, the robot obtains distance recognition necessary for evasion of the object, including data of the obstacle’s width, height, and depth by calculating the angles of images taken by the CCD camera. We applied the system to a robot in an indoor environment and evaluated its performance, and we consider the resulting problems in the discussion of our experimental results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Distributed control of simulated autonomous mobile robot collectives in payload transportation

A behavior-based control paradigm that allows a distributed collection of autonomous mobile robots to control the lifting and lowering processes of payload transportation is proposed and then tested with computer simulations. This control paradigm, which represents an approach to solving the cooperative load-bearing problem inherent in multi-agent payload transportation, is based upon a control structure we term thebehavior pathway controller. The behavior pathway controller emphasizes simple, feasible methodologies over complex, optimal methodologies, although we show that with some global self-organization of the collective, the feasible solutions approach and become optimal solutions. Using this controller in simulated environments, our robots demonstrate an ability to function with inaccurate sensor data, which is an important consideration for real world implementations of an autonomous mobile robot control paradigm. The simulated robots also demonstrate an ability to learn their place, or role, within the collective. They must learn their relative roles because they possess no predetermined knowledge about pallet mass, pallet inertia, collective size, or their positions relative to the pallet's center of gravity.     

Selection of modeling coordinates for forward dynamic multibody simulations

Modeling mechanical systems in a manner that allows the models to be simulated quickly is vital in many fields, such as real-time simulation and control. Modeling these systems using their symbolic equations, rather than the more widely-used numerical methods, generally produces faster solution times. However, the number, complexity, and computational efficiency of these equations is highly dependent upon which coordinate set was used to model the system. Most coordinate selection methods established thus far are based on the assumption that minimizing the number of modeling coordinates will produce models with faster simulation times. This paper will show that this technique is not always valid and proposes a new technique of selecting a system’s coordinates based on a series of heuristics. A large part of these heuristics will be established by closely analyzing a specific technique used to formulate a system’s equations, and the effect each step of this formulation process will have on the complexity of the final system equations.     

基于情感与环境认知的移动机器人自主导航控制

将基于情感和认知的学习与决策模型引入到基于行为的移动机器人控制体系中, 设计了一种新的自主导航控制系统. 将动力学系统方法用于基本行为设计, 并利用ART2神经网络实现对连续的环境感知状态的分类, 将分类结果作为学习与决策算法中的环境认知状态. 通过在线情感和环境认知学习, 形成合理的行为协调机制. 仿真表明, 情感和环境认知能明显地改善学习和决策过程效率, 提高基于行为的移动机器人在未知环境中的自主导航能力     

Explanation in Recommender Systems

There is increasing awareness in recommender systems research of the need to make the recommendation process more transparent to users. Following a brief review of existing approaches to explanation in recommender systems, we focus in this paper on a case-based reasoning (CBR) approach to product recommendation that offers important benefits in terms of the ease with which the recommendation process can be explained and the system’s recommendations can be justified. For example, recommendations based on incomplete queries can be justified on the grounds that the user’s preferences with respect to attributes not mentioned in her query cannot affect the outcome. We also show how the relevance of any question the user is asked can be explained in terms of its ability to discriminate between competing cases, thus giving users a unique insight into the recommendation process.     

Application of GMDH algorithms in the obstacle recognition problem for autonomous mobile robots

The basic principles of designing the control system for autonomous mobile robots (AMRs) on the basis of the inductive approach are considered. The key problem in the autonomous motion control is the recognition of obstacles. A close relationship of the obstacle recognition problem with other control problems for AMRs is demonstrated. A generalized structure, a scheme for processing information about objects as applied to the obstacle recognition problem, and an inductive algorithm for finding the control law are proposed. Aleksander Vasil’evich Tyryshkin. Born 1954. Graduated from the Tomsk Polytechnical Institute in 1976. Received candidate’s degree in engineering in 1990. Assistant professor of the Chair of Industrial Electronics at the Tomsk State University of Control Systems and Radioelectronics. Scientific interests: power and impulse electronics, automation of engineering procedures, system theory and system analysis, applied artificial intelligence. Author of 37 publications including 11 patents and inventors certificates. Awarded the Medal “400 years of Tomsk.” Anatolii Aleksandrovich Andrakhanov. Born 1982. Graduated from the Tomsk State University of Control Systems and Radioelectronics in 2004. Postgraduate at the Chair of Industrial Electronics at the same university. Scientific interests: microprocessor engineering, system theory and system analysis, mathematical methods and algorithms of artificial intelligence. Author of 10 papers.     

Using obstacle analysis to identify contingency requirements on an unpiloted aerial vehicle

This paper describes the use of Obstacle Analysis to identify anomaly handling requirements for a safety-critical, autonomous system. The software requirements for the system evolved during operations due to an on-going effort to increase the autonomous system’s robustness. The resulting increase in autonomy also increased system complexity. This investigation used Obstacle Analysis to identify and to reason incrementally about new requirements for handling failures and other anomalous events. Results reported in the paper show that Obstacle Analysis complemented standard safety-analysis techniques in identifying undesirable behaviors and ways to resolve them. The step-by-step use of Obstacle Analysis identified potential side effects and missing monitoring and control requirements. Adding an Availability Indicator and feature-interaction patterns proved useful for the analysis of obstacle resolutions. The paper discusses the consequences of these results in terms of the adoption of Obstacle Analysis to analyze anomaly handling requirements in evolving systems.     

Bipedal walking gait generation based on the Sequential Method of Analytical Potential (SMAP)

This paper presents a method we have called the Sequential Method of Analytical Potential (SMAP). By taking account of a system’s actual capabilities via Dynamic Propulsion Potentials (DPP), this method aims to generate dynamic walking gaits for bipedal robots. The objective is to move the robot by acting directly on the actuator forces. The various accelerations governing the movements of the robot are controlled by direct, precise modification of its own dynamic effects, taking account of the robot’s intrinsic dynamics as well as the capabilities of the actuators moving the joints.     

A capabilities-based model for adaptive organizations

Multiagent systems have become popular over the last few years for building complex, adaptive systems in a distributed, heterogeneous setting. Multiagent systems tend to be more robust and, in many cases, more efficient than single monolithic applications. However, unpredictable application environments make multiagent systems susceptible to individual failures that can significantly reduce its ability to accomplish its overall goal. The problem is that multiagent systems are typically designed to work within a limited set of configurations. Even when the system possesses the resources and computational power to accomplish its goal, it may be constrained by its own structure and knowledge of its member’s capabilities. To overcome these problems, we are developing a framework that allows the system to design its own organization at runtime. This paper presents a key component of that framework, a metamodel for multiagent organizations named the Organization Model for Adaptive Computational Systems. This model defines the requisite knowledge of a system’s organizational structure and capabilities that will allow it to reorganize at runtime and enable it to achieve its goals effectively in the face of a changing environment and its agent’s capabilities.     

Making it easier for older people to talk to smart homes: the effect of early help prompts

It is well known that help prompts shape how users talk to spoken dialogue systems. This study investigated the effect of help prompt placement on older users’ interaction with a smart home interface. In the dynamic help condition, help was only given in response to system errors; in the inherent help condition, it was also given at the start of each task. Fifteen older and sixteen younger users interacted with a smart home system using two different scenarios. Each scenario consisted of several tasks. The linguistic style users employed to communicate with the system (interaction style) was measured using the ratio of commands to the overall utterance length (keyword ratio) and the percentage of content words in the user’s utterance that could be understood by the system (shared vocabulary). While the timing of help prompts did not affect the interaction style of younger users, it was early task-specific help supported older users in adapting their interaction style to the system’s capabilities. Well-placed help prompts can significantly increase the usability of spoken dialogue systems for older people.     

Preventive maintenance scheduling for repairable system with deterioration

Maintenance as an important part in manufacturing system can keep equipment in good condition. Many maintenance policies help to decrease the unexpected failures and reduce high operational cost such as conventional preventive maintenance. But these conventional preventive maintenance policies have the same time interval T that may easily neglect system’s reliability, because the system deteriorates with increased usage and age. Hence, this study has developed a reliability-centred sequential preventive maintenance model for monitored repairable deteriorating system. It is supposed that system’s reliability could be monitored continuously and perfectly, whenever it reaches the threshold R, the imperfect repair must be performed to restore the system. In this model, system’s failure rate function and operational cost are both considered by the effect of system’s corresponding condition, which helps to decide the optimal reliability threshold R and preventive maintenance cycle number. Finally, through case study, the simulation results show that the improved sequential preventive maintenance policy is more practical and efficient.     

Dynamics of a three-module vibration-driven system with non-symmetric Coulomb’s dry friction

In the present paper, a three-module vibration-driven system moving on a rough horizontal plane is modeled to investigate the relation among the system’s steady-state motion, external Coulomb’s dry friction force and internal excitations. Each module of the system represents a vibration-driven system composed of a rigid body and a movable internal mass. Major attention is focused on the primary resonance situation that the excitation frequency is close to the first-order natural frequency of the system. In the case that the external friction is low, the internal excitation is weak and the stick–slip motion is negligible, both methods of averaging and modal superposition are employed to study the steady-state motion of the system. Through a set of algebraic equations, an approximate value of the system’s average steady-state velocity is obtained. Several numerical examples are calculated to verify the validity of the analytical results both qualitatively and quantitatively. It is seen that big quantitative errors will appear if stick–slip motions occur. Then, two mechanisms for the possible stick–slip motions are put forward, which explain the errors on the average steady-state velocity. Numerical simulations verify our analysis on the stick–slip effects and their mechanisms. Finally, to maximize the average steady-state velocity of the system, optimal control problem is studied. It is shown that, in addition to modifying the friction coefficients, the improvement of the system’s efficiency can be provided by changing the initial phase shifts among the three internal excitations.     

Algebraic nonrobustness conditions

We consider systems with small gain and phase margins (nonrobust systems). We obtain conditions on roots and coefficients of characteristic polynomials for open- and closed-loop nonrobust systems. These conditions are used to find the boundaries of modal control pole placement regions that guarantee a system’s robustness.     

Simulation model of general human and humanoid motion

In the last decade we have witnessed a rapid growth of Humanoid Robotics, which has already constituted an autonomous research field. Humanoid robots (or simply humanoids) are expected in all situations of humans’ everyday life, “living” and cooperating with us. They will work in services, in homes, and hospitals, and they are even expected to get involved in sports. Hence, they will have to be capable of doing diverse kinds of tasks. This forces the researchers to develop an appropriate mathematical model to support simulation, design, and control of these systems. Another important fact is that today’s, and especially tomorrow’s, humanoid robots will be more and more humanlike in their shape and behavior. A dynamic model developed for an advanced humanoid robot may become a very useful tool for the dynamic analysis of human motion in different tasks (walking, running and jumping, manipulation, various sports, etc.). So, we derive a general model and talk about a human-and-humanoid simulation system. The basic idea is to start from a human/humanoid considered as a free spatial system (“flier”). Particular problems (walking, jumping, etc.) are then considered as different contact tasks – interaction between the flier and various objects (being either single bodies or separate dynamic systems).     

Cooperation without deliberation: A minimal behavior-based approach to multi-robot teams

While terminology and some concepts of behavior-based robotics have become widespread, the central ideas are often lost as researchers try to scale behavior to higher levels of complexity. “Hybrid systems” with model-based strategies that plan in terms of behaviors rather than simple actions have become common for higher-level behavior. We claim that a strict behavior-based approach can scale to higher levels of complexity than many robotics researchers assume, and that the resulting systems are in many cases more efficient and robust than those that rely on “classical AI” deliberative approaches. Our focus is on systems of cooperative autonomous robots in dynamic environments. We will discuss both claims that deliberation and explicit communication are necessary to cooperation and systems that cooperate only through environmental interaction. In this context we introduce three design principles for complex cooperative behavior—minimalism, statelessness and tolerance—and present a RoboCup soccer system that matches the sophistication of many deliberative soccer systems while exceeding their robustness, through the use of strict behavior-based techniques with no explicit communication.