| 1. |
- Göbelbecker, Moritz, et al.
(författare)
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Dora: A Robot that Plans and Acts Under Uncertainty
- 2012
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Ingår i: Proceedings of the 35th German Conference on Artificial Intelligence (KI’12).
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Konferensbidrag (refereegranskat)abstract
- Dealing with uncertainty is one of the major challenges when constructing autonomous mobile robots. The CogX project addressed key aspects of that by developing and implementing mechanisms for self-understanding and self-extension -- i.e. awareness of gaps in knowledge, and the ability to reason and act to fill those gaps. We discuss our robot called Dora, a showcase outcome of that project. Dora is able to perform a variety of search tasks in unexplored environments. One of the results of the project is the Dora robot, that can perform a variety of search tasks in unexplored environments by exploiting probabilistic knowledge representations while retaining efficiency by using a fast planning system.
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| 2. |
- Hanheide, Marc, et al.
(författare)
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A Framework for Goal Generation and Management
- 2010
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Ingår i: Proceedings of the AAAI Workshop on Goal-Directed Autonomy.
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Konferensbidrag (refereegranskat)abstract
- Goal-directed behaviour is often viewed as an essential char- acteristic of an intelligent system, but mechanisms to generate and manage goals are often overlooked. This paper addresses this by presenting a framework for autonomous goal gener- ation and selection. The framework has been implemented as part of an intelligent mobile robot capable of exploring unknown space and determining the category of rooms au- tonomously. We demonstrate the efficacy of our approach by comparing the performance of two versions of our inte- grated system: one with the framework, the other without. This investigation leads us conclude that such a framework is desirable for an integrated intelligent system because it re- duces the complexity of the problems that must be solved by other behaviour-generation mechanisms, it makes goal- directed behaviour more robust in the face of a dynamic and unpredictable environments, and it provides an entry point for domain-specific knowledge in a more general system.
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| 3. |
- Hanheide, Marc, et al.
(författare)
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Exploiting probabilistic knowledge under uncertain sensing for efficient robot behaviour
- 2011
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Ingår i: 22nd International Joint Conference on Artificial Intelligence.
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Konferensbidrag (refereegranskat)abstract
- Robots must perform tasks efficiently and reliably while acting under uncertainty. One way to achieve efficiency is to give the robot common-sense knowledge about the structure of the world. Reliable robot behaviour can be achieved by modelling the uncertainty in the world probabilistically. We present a robot system that combines these two approaches and demonstrate the improvements in efficiency and reliability that result. Our first contribution is a probabilistic relational model integrating common-sense knowledge about the world in general, with observations of a particularenvironment. Our second contribution is a continual planning system which isable to plan in the large problems posed by that model, by automatically switching between decision-theoretic and classical procedures. We evaluate our system on objects earch tasks in two different real-world indoor environments. By reasoning about the trade-offs between possible courses of action with different informational effects, and exploiting the cues and general structures of those environments, our robot is able to consistently demonstrate efficient and reliable goal-directed behaviour.
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| 4. |
- Hanheide, Marc, et al.
(författare)
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Robot task planning and explanation in open and uncertain worlds
- 2015
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Ingår i: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921.
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Tidskriftsartikel (refereegranskat)abstract
- A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete information, and to handle task failure intelligently. This paper shows how to achieve this. There are two central ideas. The first idea is to organize the robot's knowledge into three layers: instance knowledge at the bottom, commonsense knowledge above that, and diagnostic knowledge on top. Knowledge in a layer above can be used to modify knowledge in the layer(s) below. The second idea is that the robot should represent not just how its actions change the world, but also what it knows or believes. There are two types of knowledge effects the robot's actions can have: epistemic effects (I believe X because I saw it) and assumptions (I'll assume X to be true). By combining the knowledge layers with the models of knowledge effects, we can simultaneously solve several problems in robotics: (i) task planning and execution under uncertainty; (ii) task planning and execution in open worlds; (iii) explaining task failure; (iv) verifying those explanations. The paper describes how the ideas are implemented in a three-layer architecture on a mobile robot platform. The robot implementation was evaluated in five different experiments on object search, mapping, and room categorization.
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| 5. |
- Hawes, Nick, et al.
(författare)
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Dora The Explorer : A Motivated Robot
- 2009
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Ingår i: Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010). ; , s. 1617-1618
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Konferensbidrag (refereegranskat)abstract
- Dora the Explorer is a mobile robot with a sense of curios- ity and a drive to explore its world. Given an incomplete tour of an indoor environment, Dora is driven by internal motivations to probe the gaps in her spatial knowledge. She actively explores regions of space which she hasn't previously visited but which she expects will lead her to further unex- plored space. She will also attempt to determine the cate- gories of rooms through active visual search for functionally important objects, and through ontology-driven inference on the results of this search.
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| 6. |
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| 7. |
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| 8. |
- Kucner, Tomasz Piotr, et al.
(författare)
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Survey of maps of dynamics for mobile robots
- 2023
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Ingår i: The international journal of robotics research. - : Sage Publications. - 0278-3649 .- 1741-3176. ; 42:11, s. 977-1006
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Tidskriftsartikel (refereegranskat)abstract
- Robotic mapping provides spatial information for autonomous agents. Depending on the tasks they seek to enable, the maps created range from simple 2D representations of the environment geometry to complex, multilayered semantic maps. This survey article is about maps of dynamics (MoDs), which store semantic information about typical motion patterns in a given environment. Some MoDs use trajectories as input, and some can be built from short, disconnected observations of motion. Robots can use MoDs, for example, for global motion planning, improved localization, or human motion prediction. Accounting for the increasing importance of maps of dynamics, we present a comprehensive survey that organizes the knowledge accumulated in the field and identifies promising directions for future work. Specifically, we introduce field-specific vocabulary, summarize existing work according to a novel taxonomy, and describe possible applications and open research problems. We conclude that the field is mature enough, and we expect that maps of dynamics will be increasingly used to improve robot performance in real-world use cases. At the same time, the field is still in a phase of rapid development where novel contributions could significantly impact this research area.
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| 9. |
- Molina, Sergi, et al.
(författare)
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The ILIAD Safety Stack : Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots
- 2023
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Ingår i: IEEE robotics & automation magazine. - : IEEE. - 1070-9932 .- 1558-223X.
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Tidskriftsartikel (refereegranskat)abstract
- Current intralogistics services require keeping up with e-commerce demands, reducing delivery times and waste, and increasing overall flexibility. As a consequence, the use of automated guided vehicles (AGVs) and, more recently, autonomous mobile robots (AMRs) for logistics operations is steadily increasing.
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| 10. |
- Palmieri, Luigi, et al.
(författare)
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Guest Editorial : Introduction to the Special Issue on Long-Term Human Motion Prediction
- 2021
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Ingår i: IEEE Robotics and Automation Letters. - : IEEE Press. - 2377-3766. ; 6:3, s. 5613-5617
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The articles in this special section focus on long term human motion prediction. This represents a key ability for advanced autonomous systems, especially if they operate in densely crowded and highly dynamic environments. In those settings understanding and anticipating human movements is fundamental for robust long-term operation of robotic systems and safe human-robot collaboration. Foreseeing how a scene with multiple agents evolves over time and incorporating predictions in a proactive manner allows for novel ways of planning and control, active perception, or humanrobot interaction. Recent planning and control approaches use predictive techniques to better cope with the dynamics of the environment, thus allowing the generation of smoother and more legible robot motion. Predictions can be provided as input to the planning or optimization algorithm (e.g. as a cost term or heuristic function), or as additional dimension to consider in the problem formulation (leading to an increased computational complexity). Recent perception techniques deeply interconnect prediction modules with detection, segmentation and tracking, to generally increase the accuracy of different inference tasks, i.e. filtering, predicting. As also indicated by some of the scientific works accepted in this special issue, novel deep learning architectures allow better interleaving of the aforementioned units.
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| 11. |
- Walters, Michael L., et al.
(författare)
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Evaluating the Robot Personality and Verbal Behavior of Domestic Robots Using Video-Based Studies
- 2011
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Ingår i: Advanced Robotics. - 0169-1864 .- 1568-5535. ; 25:18, s. 2233-2254
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Tidskriftsartikel (refereegranskat)abstract
- Robots are increasingly being used in domestic environments and should be able to interact with inexperienced users. Human-human interaction and human-computer interaction research findings are relevant, but often limited because robots are different from both humans and computers. Therefore, new human-robot interaction (HRI) research methods can inform the design of robots suitable for inexperienced users. A video-based HRI (VHRI) methodology was here used to carry out a multi-national HRI user study for the prototype domestic robot BIRON (BIelefeld RObot companioN). Previously, the VHRI methodology was used in constrained HRI situations, while in this study HRIs involved a series of events as part of a 'home-tour' scenario. Thus, the present work is the first study of this methodology in extended HRI contexts with a multi-national approach. Participants watched videos of the robot interacting with a human actor and rated two robot behaviors (Extrovert and Introvert). Participants' perceptions and ratings of the robot's behaviors differed with regard to both verbal interactions and person following by the robot. The study also confirms that the VHRI methodology provides a valuable means to obtain early user feedback, even before fully working prototypes are available. This can usefully guide the future design work on robots, and associated verbal and non-verbal behaviors.
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| 12. |
- Wyatt, Jeremy L., et al.
(författare)
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Self-Understanding and Self-Extension : A Systems and Representational Approach
- 2010
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Ingår i: IEEE T AUTON MENT DE. - 1943-0604. ; 2:4, s. 282-303
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Tidskriftsartikel (refereegranskat)abstract
- There are many different approaches to building a system that can engage in autonomous mental development. In this paper, we present an approach based on what we term self-understanding, by which we mean the explicit representation of and reasoning about what a system does and does not know, and how that knowledge changes under action. We present an architecture and a set of representations used in two robot systems that exhibit a limited degree of autonomous mental development, which we term self-extension. The contributions include: representations of gaps and uncertainty for specific kinds of knowledge, and a goal management and planning system for setting and achieving learning goals.
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| 13. |
- Yuan, Fang, et al.
(författare)
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Laser-Based Navigation Enhanced with 3D Time-of-Flight Data
- 2009
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Ingår i: Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. - Washington, DC : IEEE Computer Society. - 9781424427888 - 9781424427895 ; , s. 2844-2850
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Konferensbidrag (refereegranskat)abstract
- Navigation and obstacle avoidance in robotics using planar laser scans has matured over the last decades. They basically enable robots to penetrate highly dynamic and populated spaces, such as people's home, and move around smoothly. However, in an unconstrained environment the twodimensional perceptual space of a fixed mounted laser is not sufficient to ensure safe navigation. In this paper, we present an approach that pools a fast and reliable motion generation approach with modern 3D capturing techniques using a Timeof-Flight camera. Instead of attempting to implement full 3D motion control, which is computationally more expensive and simply not needed for the targeted scenario of a domestic robot, we introduce a "virtual laser". For the originally solely laserbased motion generation the technique of fusing real laser measurements and 3D point clouds into a continuous data stream is 100% compatible and transparent. The paper covers the general concept, the necessary extrinsic calibration of two very different types of sensors, and exemplarily illustrates the benefit which is to avoid obstacles not being perceivable in the original laser scan.
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