| 1. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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A Qualitative Model of Dynamic Scene Analysis and Interpretation in Ambient Intelligence Systems
- 2009
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Ingår i: International Journal of Robotics and Automation. - : ACTA Press. - 0826-8185 .- 1925-7090. ; 24:3, s. 235-244
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Tidskriftsartikel (refereegranskat)abstract
- Ambient intelligence environments necessitate representing and reasoning about dynamic spatial scenes and configurations. The ability to perform predictive and explanatory analyses of spatial scenes is crucial towards serving a useful intelligent function within such environments. We present a formal qualitative model that combines existing qualitative theories about space with it formal logic-based calculus suited to modelling dynamic environments, or reasoning about action and change in general. With this approach, it is possible to represent and reason about arbitrary dynamic spatial environments within a unified framework. We clarify and elaborate on our ideas with examples grounded in a smart environment.
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| 2. |
- Daniluk, S., et al.
(författare)
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An advice mechanism for heterogeneous robot teams
- 2020
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Ingår i: International Journal of Robotics and Automation. - : ACTA Press. - 0826-8185 .- 1925-7090. ; 35:1, s. 53-68
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an advice mechanism compatible with heterogeneous advisers that incorporates advice into the advisee's policy via a method guaranteeing convergence to an optimal policy. Further, the mechanism has the capability to use multiple advisers at each time step and decide when advice should be requested and accepted, such that the use of advice decreases over time. Experiments are formed with a simulated team of heterogeneous robots performing a foraging task. We show that the proposed mechanism can provide a performance improvement for homogeneous and heterogeneous robot teams, and the use of advice decreases over time.
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| 3. |
- Martin, Adrian, et al.
(författare)
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A dynamically distributed control framework for robot teams
- 2014
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Ingår i: International Journal of Robotics and Automation. - 0826-8185. ; 29:3, s. 312-318
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Tidskriftsartikel (refereegranskat)abstract
- This paper discusses an implementation of a versatile architecture, labelled as HAA (Host, Avatar, Agent), using provably correct distributed algorithms. The HAA architecture lays a foundation on which virtually any type of control system can be built, while providing features such as dynamically distributed processing, distributed database, and failure recovery. The algorithms for the key components of the architecture are specified, including host membership service, agent allocation, agent transfer, and agent recovery. The first component controls the processing network, while the second component oversees the dynamic distribution of processes. The third component ensures that processes are transparently transferred without any loss of data, and the fourth component facilitates the recovery of failed processes. The real-time performance of the algorithms was measured in experiments for mapping, exploration, and foraging and proved to be effective for the system sizes tested.
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| 4. |
- Martin, Adrian, et al.
(författare)
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Just-in-time cooperative simultaneous localization and mapping : A robust particle filter approach
- 2014
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Ingår i: International Journal of Robotics and Automation. - 0826-8185. ; 29:2, s. 119-132
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Tidskriftsartikel (refereegranskat)abstract
- A new approach to simultaneous localization and mapping (SLAM) using particle filters has been developed to address the issue of limited and changing processing resources in autonomous exploration tasks. This algorithm is able to store and integrate historical data after the fact to improve current estimates and to delay weight processing until it is required. The foundation of the approach is developed here and is proposed as a new strategy that can complement many existing particle filter SLAM algorithms. The algorithm is demonstrated in a Cooperative SLAM implementation with an occupancy grid map. Simulation results show a 17% reduction in exploration time compared to two traditional SLAM approaches.
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