Towards stratified model-based environmental visual perception for humanoid robots

An autonomous environmental visual perception approach for humanoid robots is presented. The proposed framework exploits the available model information and the context acquired during global localization by establishing a vision-model coupling in order to overcome the limitations of purely data-driven approaches in object recognition and surrounding status assertion. The exploitation of the model-vision coupling through the properceptive components is the key element to solve complex visual assertion-queries with proficient performance. An experimental evaluation with the humanoid robot ARMAR-IIIa is presented.     

Two-dimensional motion-planning for nonholonomic robots using the bump-surfaces concept

In this paper, a new method is introduced for finding a near-optimal path of a nonholonomic robot moving in a 2D environment cluttered with static obstacles. The method is based on the Bump-Surfaces concept and is able to deal with robots represented by a translating and rotating rigid body. The proposed approach is applied to car-like robots.     

Behavioral task processing for cognitive robots using artificial emotions

This paper presents an artificial emotional-cognitive system-based autonomous robot control architecture for a four-wheel driven and four-wheel steered mobile robot. Discrete stochastic state-space mathematical model is considered for behavioral and emotional transition processes of the autonomous mobile robot in the dynamic realistic environment. The term of cognitive mechanism system which is composed from rule base and reinforcement self-learning algorithm explain all of the deliberative events such as learning, reasoning and memory (rule spaces) of the autonomous mobile robot. The artificial cognitive model of autonomous robot control architecture has a dynamic associative memory including behavioral transition rules which are able to be learned for achieving multi-objective robot tasks. Motivation module of architecture has been considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors for long-term action planning. Also reinforcement self-learning and reasoning ability of artificial cognitive model and motivational gain effects of proposed architecture can be observed on the executing behavioral sequences during simulation. The posture and speed of the robot and the configurations, speeds and torques of the wheels and all deliberative and cognitive events can be observed from the simulation plant and virtual reality viewer. This study constitutes basis for the multi-goal robot tasks and artificial emotions and cognitive mechanism-based behavior generation experiments on a real mobile robot.     

Multi-level cognitive machine-learning based concept for human-like “artificial” walking: Application to autonomous stroll of humanoid robots

We propose a machine-learning based multi-level cognitive model inspired from early-ages’ cognitive development of human’s locomotion skills for humanoid robot’s walking modeling. Contrary to the most of already introduced works dealing with biped robot’s walking modeling, which place the problem within the context of controlling specific kinds of biped robots, the proposed model attends to a global concept of biped walking ability’s construction independently from the robot to which the concept may be applied. The chief-benefit of the concept is that the issued machine-learning based structure takes advantage from “learning” capacity and “generalization” propensity of such models: allowing a precious potential to deal with high dimensionality, nonlinearity and empirical proprioceptive or exteroceptive information. Case studies and validation results are reported and discussed evaluating potential performances of the proposed approach.     

A feedforward decoupling concept for the control of elastic robots

A reference-oriented procedure for controlling elastic robots is presented. This affords, in a first step, an optimal path planning method generating the reference trajectory. It will be realized by a classical feedforward decoupling scheme. The elastic deviations from this reference are corrected within the feedforward loop by calculation of the joint correction angles putting back the endpoint to its nominal position. In a final step, elastic vibrations of the arms are damped by an additional joint output control system, which uses as an input joint kinematics and strain gauge measurements of the elastic curvatures. The concept has been realized for a laboratory manipulator. Theory and experiments agree very well.     

A combined approach for improving humanoid robots autonomous cognitive capabilities

Recent technologies advancements promise to change our lives dramatically in the near future. A new different living society is progressively emerging, witnessed from the conception of novel digital ecosystems, where humans are expected to share their own spaces and habits with machines. Humanoid robots are more and more being developed and provided with enriched functionalities; however, they are still lacking in many ways. One important goal in this sense is to enrich their cognitive capabilities, to make them more “intelligent” in order to better support humans in both daily and special activities. The goal of this research is to set a step in bridging the gap between symbolic AI and connectionist approaches in the context of knowledge acquisition and conceptualization. Hence, we present a combined approach based on semantics and machine learning techniques for improving robots cognitive capabilities. This is part of a wider framework that covers several aspects of knowledge management, from representation and conceptualization, to acquisition, sharing and interaction with humans. Our focus in this work is in particular on the development and implementation of techniques for knowledge acquisition. Such techniques are discussed and validated through experiments, carried out on a real robotic platform, showing the effectiveness of our approach. The results obtained confirmed that the combination of the approaches gives superior performance with respect to when they are considered individually.

     

Towards a cognitive foundation for knowledge representation

Abstract. Knowledge engineering, knowledge management and conceptual modelling are concerned with representing knowledge of business and organizational domains. These research areas use ontologies for knowledge representation. Ontologies are understood either in the philosophical sense as firm metaphysical commitments or in the looser sense of dictionaries or taxonomies.
This paper critically examines the understanding and use of ontologies and knowledge representation languages in information systems (IS) research and application. As ontologies are intended to be conceptualizations of a perceived reality, they should reflect the empirically observed reality. This motivates proposing psychology of language as a reference discipline for knowledge engineering and knowledge management. Natural language is argued to reflect the cognitive concepts we use to think about and perceive the world around us. These cognitive concepts are the relevant terms with which to structure and represent knowledge about the world.
Psychology of language can provide empirical justification for a particular set of concepts to represent knowledge. This paper draws on psycho-linguistic research to develop a proposal for a system of cognitive structures. This is argued to provide the relevant concepts on which to found knowledge representation schemata for knowledge engineering, knowledge management and conceptual modelling.     

Towards nonadaptive and adaptive control of manipulation robots

Control synthesis for robotic systems with a variable payload is considered. First, we synthesize a robust, nonadaptive decentralized control using an approximative system model. Then, we analyze the stability of an exact system model. We thus check whether the robotic manipulator is stabilized for all allowable payload variations. If the simple decentralized control cannot accommodate all expected payload variations we introduce additional load, nonadaptive, feedback loop. This global control requires force transducers to be implemented in manipulator joints. If such nonadaptive control cannot stabilize robotic manipulator trajectories we suggest another adaptive control scheme. This control scheme includes an algorithm for on-line identification of variable payload and adaptation of local gains.     

Towards principled experimental study of autonomous mobile robots

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.     

Towards cooperation of heterogeneous,autonomous robots: A case study of humanoid and wheeled robots

In this paper a case study of the cooperation of a strongly heterogeneous autonomous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some redundant abilities is presented. By combining strongly heterogeneous robots the diversity of achievable tasks increases as the variety of sensing and motion abilities of the robot system is extended, compared to a usually considered team of homogeneous robots. A number of methodologies and technologies required in order to achieve the long-term goal of cooperation of heterogeneous autonomous robots are discussed, including modeling tasks and robot abilities, task assignment and redistribution, robot behavior modeling and programming, robot middleware and robot simulation. Example solutions and their application to the cooperation of autonomous wheeled and humanoid robots are presented in this case study. The scenario describes a tightly coupled cooperative task, where the humanoid robot and the wheeled robot track a moving ball, which is to be approached and kicked by the humanoid robot into a goal. The task can be fulfilled successfully by combining the abilities of both robots.     

Dead reckoning for biped robots that suffers less from foot contact condition based on anchoring pivot estimation

A novel technique of dead reckoning for high-rate feedback control of biped robots is proposed. A fast position estimation of a robot is achieved by fusing information only from internal sensors including joint angle encoders, inertial sensors and force sensors. It combines the kinematics computation and the double integral of acceleration in a complementary way in order to improve the accuracy. The kinematics computation takes the movement of supporting foot, particularly, rotation about a fixed point and rolling on the terrain into consideration. The weights on each information are adjusted automatically based on the reaction force from the ground as it is expected to reflect the certainty of the contact condition of each foot. The validity of the proposed method is verified through computer simulations.     

Towards cognitive evaluation of computer-drawn sketches

This paper seeks to raise visual comparisons beyond subjective opinions into evidence-based visual reasoning. It provides an informal deductive analysis of the marks in sketches derived with two competing line-filtering algorithms. This prompted the novel speculation that the visual system might be placing some types of anomalies in the foreground of mental 3D space, where they can be ignored. A brief survey is provided to encourage informed debate. Although the proposed cognitive computation was not automated, it justified the rejection of the Douglas–Peucker algorithm in favour of Visvalingam's algorithm in subsequent research within the Cartographic Information Systems Research Group (CISRG).     

Survey of locomotion control of legged robots inspired by biological concept

Compared with wheeled mobile robots, legged robots can easily step over obstacles and walk through rugged ground. They have more flexible bodies and therefore, can deal with complex environment. Nevertheless, some other issues make the locomotion control of legged robots a much complicated task, such as the redundant degree of freedoms and balance keeping. From literatures, locomotion control has been solved mainly based on programming mechanism. To use this method, walking trajectories for each leg and the...     

Programming for cognitive justice: Towards an ethical framework for democratic code

This paper contrasts two approaches to knowledge sharing for socio-economic development to examine how assumptions about knowledge are reflected in computer-based information systems. The paper argues that socio-technical systems for global knowledge sharing posses a bias resulting from choices about technology and from assumptions about knowledge, and that this bias may adversely affect the diversity of knowledge. To overcome this bias, the concept of cognitive justice is proposed and, on this basis, a framework suggested to guide the design of information systems based on a principle of the equal validity of all knowledges.     

Perception network for the team of indoor mobile robots: concept,architecture, implementation

The concept of perception network with application to the distributed perception processes taking place among mobile robots operating on the shared shop-floor is discussed. Its relationship with the distributed environment modeling is pointed out. The concept of geometrical database is combined with multiple classes of maps generated with particular physical sensors, in order to obtain the world model. The logical and functional structure of the perception network has been proposed to reflect the semantics of the transportation system consisting of the team of indoor mobile robots.