| 1. |
- Tomic, Stevan, 1981-, et al.
(author)
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Towards Institutions for Mixed Human-Robot Societies
- 2018
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In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, (AAMAS' 18). - : Association for Computing Machinery (ACM). - 9781450356497 ; , s. 2216-2217
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Conference paper (peer-reviewed)abstract
- We report an exploration into normative reasoning for robots in human societies using the concept of institutions.
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| 2. |
- Trincavelli, Marco
(author)
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Gas discrimination for mobile robots
- 2010
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Doctoral thesis (other academic/artistic)abstract
- The problem addressed in this thesis is discrimination of gases with an array of partially selective gas sensors. Metal oxide gas sensors are the most common gas sensing technology since they have, compared to other gas sensing technologies, a high sensitivity to the target compounds, a fast response time,they show a good stability of the response over time and they are commercially available. One of the most severe limitation of metal oxide gas sensors is the scarce selectivity, that means that they do not respond only to the compound for which they are optimized but also to other compounds. One way to enhance the selectivity of metal oxide gas sensors is to build an array of sensorswith different, and partially overlapping, selectivities and then analyze the response of the array with a pattern recognition algorithm. The concept of anarray of partially selective gas sensors used together with a pattern recognition algorithm is known as an electronic nose (e-nose).In this thesis the attention is focused on e-nose applications related mobile robotics. A mobile robot equipped with an e-nose can address tasks like environmental monitoring, search and rescue operations or exploration of hazardous areas. In e-noses mounted on mobile robots the sensing array is most often directly exposed to the environment without the use of a sensing chamber.This choice is often made because of constraints in weight, costs and because the dynamic response obtained by the direct interaction of the sensors with the gas plume contains valuable information. However, this setup introduces additional challenges due to the gas dispersion that characterize natural environments.Turbulent and chaotic gas dispersal causes the array of sensors to be exposed to rapid changes in concentration that cause the sensor response to behighly dynamic and to seldom reach a steady state. Therefore the discriminationof gases has to be performed on features extracted from the dynamics of the signal. The problem is further complicated by variations in temperature and humidity, physical variables to which metal oxide gas sensors are crossensitive.For these reasons the problem of discrimination of gases when an array of sensors is directly exposed to the environment is different from when the array of sensors is in a controlled chamber. This thesis is a compilation of papers whose contributions are two folded.On one side new algorithms for discrimination of gases with an array of sensors directly exposed to the environment are presented. On the other side, innovative experimental setups are proposed. These experimental setups enable the collection of high quality data that allow a better insight in the problem of discrimination of gases with mobile robots equipped with an e-nose. The algorithmic contributions start with the design and validation of a gas discrimination algorithm for gas sensors array directly exposed to the environment. The algorithmis then further developed in order to be able to run online on a robot, thereby enabling the possibility of creating an olfactory driven path-planning strategy. Additional contributions aim at maximizing the generalization capabilitiesof the gas discrimination algorithm with respect to variations in the environmental conditions. First an approach in which the odor discrimination is performed by an ensemble of linear classifiers is considered. Then a feature selection method that aims at finding a feature set that is insensitive to variations in environmental conditions is designed. Finally, a further contribution in this thesis is the design of a pattern recognition algorithm for identification of bacteria from blood vials. In this case the array of gas sensors was deployed ina controlled sensing chamber.
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| 3. |
- Wasik, Alicja, et al.
(author)
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Towards Norm Realization in Institutions Mediating Human-Robot Societies
- 2018
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In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : IEEE. - 9781538680940 - 9781538680957 ; , s. 297-304
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Conference paper (peer-reviewed)abstract
- Social norms are the understandings that govern the behavior of members of a society. As such, they regulate communication, cooperation and other social interactions. Robots capable of reasoning about social norms are more likely to be recognized as an extension of our human society. However, norms stated in a form of the human language are inherently vague and abstract. This allows for applying norms in a variety of situations, but if the robots are to adhere to social norms, they must be capable of translating abstract norms to the robotic language. In this paper we use a notion of institution to realize social norms in real robotic systems. We illustrate our approach in a case study, where we translate abstract norms into concrete constraints on cooperative behaviors of humans and robots. We investigate the feasibility of our approach and quantitatively evaluate the performance of our framework in 30 real experiments with user-based evaluation with 40 participants.
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| 4. |
- Wiedemann, Thomas, 1988-
(author)
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Domain Knowledge Assisted Robotic Exploration and Source Localization
- 2020
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Doctoral thesis (other academic/artistic)abstract
- Deploying mobile robots to explore hazardous environments provides an advantageous way to avoid threats for human operators. For example, in situations, where airborne toxic or explosive material is leaking, robots can be dispatched to localize the leaks. This thesis investigates a novel exploration strategy to automatically localize such emission sources with multiple mobile robots that are equipped with sensors to measure the concentration of the emitted gas.The problem of localizing gas sources consists of two sub-problems that are addressed here. First, the thesis develops a method to estimate the source locations from sequences of localized concentration measurements. This approach can be also applied in case the measurements are collected by static sensor networks or human operators. Second, the thesis proposes an exploration strategy that guides mobile robots to informative measurement locations. With this strategy, a high level of autonomy is achieved and it is ensured that the collected measurements help to estimate the sources. As the main contribution, the proposed approach incorporates prior available domain knowledge about the gas dispersion process and the environment. Accordingly, the approach was coined Domain-knowledge Assisted Robotic Exploration and Source-localization (DARES). Domain knowledge is incorporated in two ways. First, the advection-diffusion Partial Differential Equation (PDE) provides a mathematical model of the gas dispersion process. A Bayesian interpretation of the PDE allows us to estimate the source distribution and to design the exploration strategy. Second, the additional assumption is exploited that the sources are sparsely distributed in the environment, even though we do not know their exact number. The Bayesian inference approach incorporates this assumption by means of a sparsity inducing prior.Simulations and experiments show that the sparsity inducing prior helps to localize the sources based on fewer measurements compared to not exploiting the sparsity assumption. Further, the DARES approach results in efficient measurement patterns of the robots, which tend to start in downwind regions and move in upwind direction towards the sources where they cluster their measurements. It is remarkable that this behavior arises naturally without explicit instructions as a result of including domain knowledge and the proposed exploration strategy.
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