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There is severe clinical vitamin A deficiency (VAD) prevalence among Ghanaians and many African countries. Foodbased diets has been suggested as a more sustainable approach to solving the VAD situation in Africa. In this study, A participatory action research between orange flesh sweet potato farmers, gari processors within central region and academia was adopted to develop gari containing provitamin A beta-carotene. Gari is a major staple for Ghanaians and people in the West African subregion due to its affordability and swelling capacity. It is mainly eaten raw with water, sugar, groundnut and milk as gari-soakings or with hot water to prepare gelatinized food called gari-kai in Ghana or “eba” among Nigerians. However, gari is limited in provitamin A carotenoids. Orange fleshed sweet potato (OFSP) is known to contain large amount of vitamin A precursor. Therefore, addition of OFSP to gari would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa. To develop this, different proportions of orange fleshed sweet potatoes (OFSP) was used to substitute cassava mash and fermented spontaneously to produce composite gari - a gritty-crispy ready-to-eat food product. Both the amount of OFSP and the fermentation duration caused significant increases in the β-carotene content of the composite gari. OFSP addition reduced the luminance while roasting made the composite gari yellower when compared with the cake used. Addition of OFSP negatively affected the swelling capacity of the gari although not significant. The taste, texture, flavour and the overall preferences for the composite gari decreased due to the addition of the OFSP but fermentation duration (FD) improved them. The sample with 10% OFSP and FD of 1.81 days was found to produce the optimal gari. One-portion of the optimal gari would contribute to 34.75, 23.2, 23.2, 27, 17 and 16% of vitamin A requirements amongst children, adolescent, adult males, adult females, pregnant women and lactating mothers respectively. The study demonstrated that partial substitution of cassava with OFSP for gari production would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa while involvement of farmers and processors prior to the design of research phase enhanced the adoption of intervention strategies.
An essential measure of autonomy in service robots designed to assist humans is adaptivity to the various contexts of human-oriented tasks. These robots may have to frequently execute the same action, but subject to subtle variations in task parameters that determine optimal behaviour. Such actions are traditionally executed by robots using pre-determined, generic motions, but a better approach could utilize robot arm maneuverability to learn and execute different trajectories that work best in each context.
In this project, we explore a robot skill acquisition procedure that allows incorporating contextual knowledge, adjusting executions according to context, and improvement through experience, as a step towards more adaptive service robots. We propose an apprenticeship learning approach to achieving context-aware action generalisation on the task of robot-to-human object hand-over. The procedure combines learning from demonstration, with which a robot learns to imitate a demonstrator’s execution of the task, and a reinforcement learning strategy, which enables subsequent experiential learning of contextualized policies, guided by information about context that is integrated into the learning process. By extending the initial, static hand-over policy to a contextually adaptive one, the robot derives and executes variants of the demonstrated action that most appropriately suit the current context. We use dynamic movement primitives (DMPs) as compact motion representations, and a model-based Contextual Relative Entropy Policy Search (C-REPS) algorithm for learning policies that can specify hand-over position, trajectory shape, and execution speed, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours.
We demonstrate the algorithm’s ability to learn context-dependent hand-over positions, and new trajectories, guided by suitable reward functions, and show that the current DMP implementation limits learning context-dependent execution speeds. We additionally conduct a user study involving participants assuming different postures and receiving an object from the robot, which executes hand-overs by either exclusively imitating a demonstrated motion, or selecting hand-over positions based on learned contextual policies and adapting its motion accordingly. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
An essential measure of autonomy in assistive service robots is adaptivity to the various contexts of human-oriented tasks, which are subject to subtle variations in task parameters that determine optimal behaviour. In this work, we propose an apprenticeship learning approach to achieving context-aware action generalization on the task of robot-to-human object hand-over. The procedure combines learning from demonstration and reinforcement learning: a robot first imitates a demonstrator’s execution of the task and then learns contextualized variants of the demonstrated action through experience. We use dynamic movement primitives as compact motion representations, and a model-based C-REPS algorithm for learning policies that can specify hand-over position, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours. We additionally conduct a user study involving participants assuming different postures and receiving an object from a robot, which executes hand-overs by either imitating a demonstrated motion, or adapting its motion to hand-over positions suggested by the learned policy. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
In this paper, the performance evaluation of Frequency Modulated Chaotic On-Off Keying (FM-COOK) in AWGN, Rayleigh and Rician fading channels is given. The simulation results show that an improvement in BER can be gained by incorporating the FM modulation with COOK for SNR values less than 10dB in AWGN case and less than 6dB for Rayleigh and Rician fading channels.
ICT integration by universities teaching professionals is emerging as a major concern, this study demonstrate the need to address the integration problem by encouraging existing metrics use in indexing ICT integration as an ICT governance strategy. Quality of integration depends on quality indexing which also depend on quality of existing metrics and their use. Considering the role that University Information Technology Teaching Professionals’ (UITTPs) continuous improvement indexing can offer, towards autonomic governance of the continuous emerging ICTs in the university teaching, this study examined extent in use of existing ICT integration metrics to index ICT integration by the UITTPs. Six metrics for ICT integration were investigated; time, workshop course content relevance, technical malfunctions, support conditions, support services, and motivation and commitment to student learning and staff professional development metrics. Descriptive survey design was used in which interviews were conducted to UITTPs in three (3) public and three (3) private purposively selected universities in Kenya. The findings were analyzed descriptively and inferentially using Kendall’s correlation of concordance and tested using Chi-square on the extent of concordance and presented with help of frequency tables, figures and percentages. The findings revealed that all the metrics are rarely used for indexing ICT integration (32.8%), and most UITTPs were in discordance on this level of all the six metrics use except for support condition. This implied that the use of metrics for indexing integration has not been formalized across the Kenyan universities. Universities need to be encouraged to identify suitable metrics, formalize them and improve their frequency in use. Secondly, socio based metrics such as content relevance are used more frequently for indexing integration as compared to Technical metrics, socio-technical metrics balance therefore need to be emphasized by the universities management when determining and using metrics for indexing ICT integration.
The design of an efficient digital circuit in term of low-power has become a very challenging issue. For this reason, low-power digital circuit design is a topic addressed in electrical and computer engineering curricula, but it also requires practical experiments in a laboratory. This PhD research investigates a novel approach, the low-power design laboratory system by developing a new technical and pedagogical system. The low-power design laboratory system is composed of two types of laboratories: the on-site (hands-on) laboratory and the remote laboratory. It has been developed at the Bonn-Rhine-Sieg University of Applied Sciences to teach low-power techniques in the laboratory. Additionally, this thesis contributes a suggestion on how the learning objectives can be complemented by developing a remote system in order to improve the teaching process of the low-power digital circuit design. This laboratory system enables online experiments that can be performed using physical instruments and obtaining real data via the internet. The laboratory experiments use a Field Programmable Gate Array (FPGA) as a design platform for circuit implementation by students and use image processing as an application for teaching low-power techniques.
This thesis presents the instructions for the low-power design experiments which use a top-down hierarchical design methodology. The engineering student designs his/her algorithm with a high level of abstraction and the experimental results are obtained and measured at a low level (hardware) so that more information is available to correctly estimate the power dissipation such as specification, latency, thermal effect, and technology used. Power dissipation of the digital system is influenced by specification, design, technology used, as well as operating temperature. Digital circuit designers can observe the most influential factors in power dissipation during the laboratory exercises in the on-site system and then use the remote system to supplement investigating the other factors. Furthermore, the remote system has obvious benefits such as developing learning outcomes, facilitating new teaching methods, reducing costs and maintenance, cost-saving by reducing the numbers of instructors, saving instructor time and simplifying their tasks, facilitating equipment sharing, improving reliability, and finally providing flexibility of usage the laboratories.
This paper describes a project carried out at the Bonn-Rhein-Sieg University to teach low-power digital design structures in a laboratory. Low-power design has become one of the most essential constraints in digital systems, especially in portable devices. For this purpose, low-power design is a topic addressed in electrical and computer curricula, but it also requires applications in a laboratory. Therefore, this project focuses on preparing students for current trends in low-power design by examining realistic applications of its basic theories and principles, either hands-on or remotely. The laboratory's experiments use a field programmable gate array (FPGA) as a design platform for implementing the students' digital designs. This contribution reports on our first experiences in teaching low-power design in the lab. This paper focuses on the educational impact on students regarding the following: (1) overall objectives in the laboratory, (2) experimental exercises with low-power techniques, and (3) using educational FPGA boards and the EduPow board. The EduPow board is a developed hands-on board at the Bonn-Rhein-Sieg University that is relatively specific on using various signal image-processing applications to directly observe the power dissipation of a student's digital algorithm. Our assessment of the low-power design lab shows that the requirements and objectives of this project are fairly well satisfied. In addition, students' feedback indicates that using the EduPow board is more attractive and motivational in their work.
For many different applications, current information about the bandwidth-related metrics of the utilized connection is very useful as they directly impact the performance of throughput sensitive applications such as streaming servers, IPTV and VoIP applications. In literature, several tools have been proposed to estimate major bandwidth-related metrics such as capacity, available bandwidth and achievable throughput. The vast majority of these tools fall into one of Packet Pair (PP), Variable Packet Size (VPS), Self-Loading of Periodic Streams (SLoPS) or Throughput approaches. In this study, seven popular bandwidth estimation tools including nettimer, pathrate, pathchar, pchar, clink, pathload and iperf belonging to these four well-known estimation techniques are presented and experimentally evaluated in a controlled testbed environment. Differently from the rest of studies in literature, all tools have been uniformly classified and evaluated according to an objective and sophisticated classification and evaluation scheme. The performance comparison of the tools incorporates not only the estimation accuracy but also the probing time and overhead caused.
YAWL (Yet Another Workflow Language) is an open source Business Process Management System, first released in 2003. YAWL grew out of a university research environment to become a unique system that has been deployed worldwide as a laboratory environment for research in Business Process Management and as a productive system in other scientific domains.
Cancer is one of the leading causes of death worldwide [183], with lung tumors being the most frequent cause of cancer deaths in men as well as one of the most common cancers diagnosed in woman [40]. As symptoms often arise in advanced stages, an early diagnosis is especially important to ensure the best and earliest possible treatment. In order to achieve this, Computed Tomography (CT) scans are frequently used for tumor detection and diagnosis. We will present examples of publicly available CT image data of lung cancer patients and discuss possible methods to realize an automatic system for automated cancer diagnosis. We will also look at the recent SPIE-AAPM Lung CT Challenge [10] data set in detail and describe possible methods and challenges for image segmentation and classification based on this data set.
With trainings and research oriented towards sustainable development since 2006 (Water and Sanitation, Infrastructure, Renewable Energies and Energy Processes), Foundation 2iE is positioning itself as a reference institute that trains innovative engineers-entrepreneurs for the needs and challenges of Africa’s development. Center of Excellence of the UEMOA and the World Bank, CSR is at the heart of the Strategy of the institute which aims to be a showcase in this field in Africa.
When users in virtual reality cannot physically walk and self-motions are instead only visually simulated, spatial updating is often impaired. In this paper, we report on a study that investigated if HeadJoystick, an embodied leaning-based flying interface, could improve performance in a 3D navigational search task that relies on maintaining situational awareness and spatial updating in VR. We compared it to Gamepad, a standard flying interface. For both interfaces, participants were seated on a swivel chair and controlled simulated rotations by physically rotating. They either leaned (forward/backward, right/left, up/down) or used the Gamepad thumbsticks for simulated translation. In a gamified 3D navigational search task, participants had to find eight balls within 5 min. Those balls were hidden amongst 16 randomly positioned boxes in a dark environment devoid of any landmarks. Compared to the Gamepad, participants collected more balls using the HeadJoystick. It also minimized the distance travelled, motion sickness, and mental task demand. Moreover, the HeadJoystick was rated better in terms of ease of use, controllability, learnability, overall usability, and self-motion perception. However, participants rated HeadJoystick could be more physically fatiguing after a long use. Overall, participants felt more engaged with HeadJoystick, enjoyed it more, and preferred it. Together, this provides evidence that leaning-based interfaces like HeadJoystick can provide an affordable and effective alternative for flying in VR and potentially telepresence drones.
The nature of the program was an exchange program between Hochschule Bonn-Rhein-Sieg, University of Applied Sciences and the University of Cape Coast. The program was advertised and we applied. We were shortlisted for interview and we were selected as the candidates for the exchange program. The program took a period of five months. We set off from Accra, Ghana to Germany on 7th September 2015, and returned to Ghana on 25th January 2016.
The role of tourism entrepreneurship in rural development continues to be a subject of interest and debate among academia and practitioners. Theoretically, it is anticipated that tourism entrepreneurship will lead to livelihood diversification, enhancement and ultimately a revitalization of the rural economy. While tourism is posited as an accessible entrepreneurship pathway, there is a dearth of information regarding rural dwellers’ actual experiences with it, especially within the Ghanaian context. Using a case study approach and qualitative data from Wli; a rural tourism destination in Ghana, this paper delves into the opportunities and concerns associated with tourism entrepreneurship in rural areas. Data was obtained between November and December 2016 from 27 persons who were either tourism enterprise owners or employees. Findings from the study showed that entrepreneurial activities centred on the provision of accommodation, food and beverage, souvenir and guiding services. The nature of the activities enabled easy transfer of existing skills and knowledge. Further, entry into tourism entrepreneurship was perceived to be easy by the majority of study participants. These findings confirm the potential for tourism to be employed in boosting entrepreneurial activities in rural areas. Nevertheless, there were concerns regarding access to credit, institutional support, unhealthy competitions, low incomes, unguaranteed pensions, and seasonality and skewness of demand. These concerns threatened the growth and sustainability of tourism entrepreneurship within the community. From a policy perspective, there is a need for institutional recognition and support for tourism entrepreneurial intentions and activities in rural areas. Practice-wise, credit facilities need to be designed specifically for tourism-related rural enterprises. Further, periodic skills and knowledge augmentation programmes must be initiated to help expand the skill sets for the rural entrepreneurs. Finally, there is a need for the formation of traderelated networks to provide a platform for knowledge and experience sharing among the entrepreneurs.
Entrepreneurship education serves a conduit for new venture creation as it provides the knowledge and skills needed to increase the self-efficacy of individuals to start and run new businesses and to grow existing ones. This study, therefore, sought to assess the relationship between the approaches to the teaching of entrepreneur-ship and entrepreneurial intention on a cohort of 292 respondents consisting of students who have studied entrepreneurship in three selected Universities. A structured questionnaire was used to obtain data randomly from students. The canonical correlation results indicate that education for and through entrepreneurship is the best approach to promoting entrepreneurial intensity among University students, if the aim of teaching entrepreneur-ship is to promote start-up activities. The findings provide valuable insights for institutions of higher learning and policy makers in Ghana with respect to the appropriate methodologies to be adopted in the teaching of entrepreneurship in our universities.
As competition for tourists becomes more global, understanding and accommodating the needs of international tourists, with their different cultural backgrounds, has become increasingly important. This study highlights the variations in tourist industry service--particularly as they relate to different cultures. Specifically, service failures experienced by Japanese and German tourists in the U.S. were categorized using the Critical Incident Technique (CIT). The results were compared with earlier studies of service failures experienced by American consumers in the tourist industry. The sample consists of 128 Japanese and 94 “Germanic” (German, Austrian, Swiss-German) respondents. The Japanese and German sample rated “Inappropriate employee behavior” most significant category of service failure. More than half of these respondents said that, because of the failure, they would avoid the offending U.S. business. This is a much stronger response than an American sample had reported in an earlier study. The implications for managers and researchers are discussed.
Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
Competency-Based Teaching Using Simulation Exercises: Evidence of the University of Cape Coast
(2018)
Tertiary institutions exist to train manpower to solve local, national, and international problems. Products from such institutions should not be a problem to countries as in the case of some Sub-Saharan African countries including Ghana which has a high level of graduate unemployment. Among the causes of the problem is the nature of teaching or the syllabus or the programs students pursue while in such institutions. The paper discusses one of the teaching strategies used to make a course relevant for a program and for the working world. In this course, students are introduced to practice-oriented learning through simulation exercises. The project activities specifically seek to assess the students’ understanding of business formation; examine students’ understanding of sustainability, creativity and innovation of business ideas; assess their understanding of the functional areas of business including marketing & sales, finance, human resource management, operations, and accounting, among others. Feedback from students who have participated indicates the exercise gave much more exposure and meaning to the concepts they learned in class. In this exercise, students build teams, develop a product, learn to set up a business, and design organogram, business vision, mission, and core values. The exercise empowers students to learn by doing. It accords students the opportunity to review their own knowledge and skills with respect to the concepts they have learned in the course. More than 3000 students have participated in this project since its inception in the academic year 2013/2014. It is estimated that 1000 students will participate in this project in the academic year 2017/2018.
Multidisciplinary, multicultural, and multitasking has taken center stage in the global educational debate. Globalization and improvement in communication have affected the way organisations operate and hence influenced whom they hire. Today, it is common practice to work with people from diverse backgrounds and it requires competencies that go beyond general project management. Intercultural awareness, networking in different global communities, and learning to develop specific communication strategies for different stakeholders is all part of the package of skills and competencies that are required in today's interconnected world. This has indirect implication on the nature of skills and competencies institutions/universities must equip their students with to enable them to compete successfully in the working world.
Conclusion
(2018)
There is a paradigm shift from traditional content-based education and training to competencybased and practice-oriented training. This shift has occurred because practice-oriented teaching has been found to produce a training outcome that is industry focused, generating the relevant occupational standards. Competency-based training program often comprises of modules broken into segments called learning outcomes. These learning outcomes are based on criteria set by industry and assessment is designed to ensure students become competent in their respective areas of specialization.
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot.We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation and robust object recognition.
Soluble CD21 (sCD21), released from the plasma membrane by proteolytic cleavage (shedding) of its extracellular domain (ectodomain) blocks B cell/follicular dendritic cell interaction and activates monocytes. We show here that both serine- and metalloproteases are involved in CD21 shedding. Using the oxidant pervanadate to mimic B cell receptor activation and thiol antioxidants such as N-acetylcysteine (NAC) and glutathione (GSH) we show that CD21 shedding is a redox-regulated process inducible by oxidation presumably through activation of a tyrosine kinase-mediated signal pathway involving protein kinase C (PKC), and by reducing agents that either directly activate the metalloprotease and/or modify intramolecular disulfide bridges within CD21 and thereby facilitate access to the cleavage site. Lack of short consensus repeat 16 (SCR16) abolishes CD21 shedding, and opening of the disulfide bridge between cys-2 (Cys941) and cys-4 (Cys968) of SCR16 is a prerequisite for CD21 shedding. Replacing these cysteines with selenocysteines (thereby changing the redox potential from -180 to -381 mV) results in a loss of inducible CD21 shedding, and removing this bridge by exchanging these cysteines with methionines increases CD21 shedding.
Estimation of Prediction Uncertainty for Semantic Scene Labeling Using Bayesian Approximation
(2018)
With the advancement in technology, autonomous and assisted driving are close to being reality. A key component of such systems is the understanding of the surrounding environment. This understanding about the environment can be attained by performing semantic labeling of the driving scenes. Existing deep learning based models have been developed over the years that outperform classical image processing algorithms for the task of semantic labeling. However, the existing models only produce semantic predictions and do not provide a measure of uncertainty about the predictions. Hence, this work focuses on developing a deep learning based semantic labeling model that can produce semantic predictions and their corresponding uncertainties. Autonomous driving needs a real-time operating model, however the Full Resolution Residual Network (FRRN) [4] architecture, which is found as the best performing architecture during literature search, is not able to satisfy this condition. Hence, a small network, similar to FRRN, has been developed and used in this work. Based on the work of [13], the developed network is then extended by adding dropout layers and the dropouts are used during testing to perform approximate Bayesian inference. The existing works on uncertainties, do not have quantitative metrics to evaluate the quality of uncertainties estimated by a model. Hence, the area under curve (AUC) of the receiver operating characteristic (ROC) curves is proposed and used as an evaluation metric in this work. Further, a comparative analysis about the influence of dropout layer position, drop probability and the number of samples, on the quality of uncertainty estimation is performed. Finally, based on the insights gained from the analysis, a model with optimal configuration of dropout is developed. It is then evaluated on the Cityscape dataset and shown to be outperforming the baseline model with an AUC-ROC of about 90%, while the latter having AUC-ROC of about 80%.
A robot (e.g. mobile manipulator) that interacts with its environment to perform its tasks, often faces situations in which it is unable to achieve its goals despite perfect functioning of its sensors and actuators. These situations occur when the behavior of the object(s) manipulated by the robot deviates from its expected course because of unforeseeable ircumstances. These deviations are experienced by the robot as unknown external faults. In this work we present an approach that increases reliability of mobile manipulators against the unknown external faults. This approach focuses on the actions of manipulators which involve releasing of an object. The proposed approach, which is triggered after detection of a fault, is formulated as a three-step scheme that takes a definition of a planning operator and an example simulation as its inputs. The planning operator corresponds to the action that fails because of the fault occurrence, whereas the example simulation shows the desired/expected behavior of the objects for the same action. In its first step, the scheme finds a description of the expected behavior of the objects in terms of logical atoms (i.e. description vocabulary). The description of the simulation is used by the second step to find limits of the parameters of the manipulated object. These parameters are the variables that define the releasing state of the object.
Using randomly chosen values of the parameters within these limits, this step creates different examples of the releasing state of the object. Each one of these examples is labelled as desired or undesired according to the behavior exhibited by the object (in the simulation), when the object is released in the state corresponded by the example. The description vocabulary is also used in labeling the examples autonomously. In the third step, an algorithm (i.e. N-Bins) uses the labelled examples to suggest the state for the object in which releasing it avoids the occurrence of unknown external faults.
The proposed N-Bins algorithm can also be used for binary classification problems. Therefore, in our experiments with the proposed approach we also test its prediction ability along with the analysis of the results of our approach. The results show that under the circumstances peculiar to our approach, N-Bins algorithm shows reasonable prediction accuracy where other state of the art classification algorithms fail to do so. Thus, N-Bins also extends the ability of a robot to predict the behavior of the object to avoid unknown external faults. In this work we use simulation environment OPENRave that uses physics engine ODE to simulate the dynamics of rigid bodies.
A system that interacts with its environment can be much more robust if it is able to reason about the faults that occur in its environment, despite perfect functioning of its internal components. For robots, which interact with the same environment as human beings, this robustness can be obtained by incorporating human-like reasoning abilities in them. In this work we use naive physics to enable reasoning about external faults in robots. We propose an approach for diagnosing external faults that uses qualitative reasoning on naive physics concepts for diagnosis. These concepts are mainly individual properties of objects that define their state qualitatively. The reasoning process uses physical laws to generate possible states of the concerned object(s), which could result into a detected external fault. Since effective reasoning about any external fault requires the information of relevant properties and physical laws, we associate different properties and laws to different types of faults which can be detected by a robot. The underlying ontology of this association is proposed on the basis of studies conducted (by other researchers) on reasoning of physics novices about everyday physical phenomena. We also formalize some definitions of properties of objects into a small framework represented in First-Order logic. These definitions represent naive concepts behind the properties and are intended to be independent from objects and circumstances. The definitions in the framework illustrates our proposal of using different biased definitions of properties for different types of faults. In this work, we also present a brief review of important contributions in the area of naive/qualitative physics. These reviews help in understanding the limitations of naive/qualitative physics in general. We also apply our approach to simple scenarios to asses its limitations in particular. Since this work was done independent of any particular real robotic system, it can be seen as a theoretical proof of the concept of usefulness of naive physics for external fault reasoning in robotics.