| 1. |
- Anisi, David A., 1977-, et al.
(författare)
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Algorithms for the connectivity constrained unmanned ground vehicle surveillance problem
- 2009
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Ingår i: European Control Conference (ECC). - Budapest, Hungary : EUCA.
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Konferensbidrag (refereegranskat)abstract
- The Connectivity Constrained UGV Surveillance Problem (CUSP) considered in this paper is the following. Given a set of surveillance UGVs and a user defined area to be covered, find waypoint-paths such that; 1) the area is completely surveyed, 2) the time for performing the search is minimized and 3) the induced information graph is kept recurrently connected. It has previously been shown that the CUSP is NP-hard. This paper presents four different heuristic algorithms for solving the CUSP, namely, the Token Station Algorithm, the Stacking Algorithm, the Visibility Graph Algorithm and the Connectivity Primitive Algorithm. These algorithms are then compared by means of Monte Carlo simulations. The conclusions drawn are that the Token Station Algorithm provides the most optimal solutions, the Stacking Algorithm has the lowest computational complexity, while the Connectivity Primitive Algorithm provides the best trade-off between optimality and computational complexity for larger problem instances.
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| 2. |
- Anisi, David A., et al.
(författare)
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Cooperative Surveillance Missions with Multiple Unmanned Ground Vehicles (UGVs)
- 2008
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Ingår i: 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008). - 9781424431243 ; , s. 2444-2449
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Konferensbidrag (refereegranskat)abstract
- This paper proposes an optimization based approach to multi-UGV surveillance. In particular, we formulate both the minimum time- and connectivity constrained surveillance problems, show NP-hardness of them and propose decomposition techniques that allow us to solve them efficiently in an algorithmic manner. The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a path and such that the time for executing the search in parallel is minimized. Here, the sensor's field of view are assumed to be occluded by the obstacles and limited by a maximal sensor range. The connectivity constrained formulation extends the first by additionally requiring that the information graph induced by the sensors is connected at the time instants when the UGVs stop to perform the surveillance task. The second formulation is relevant to situation when mutual visibility is needed either to transmit the sensor data being gathered, or to protect the team from hostile persons trying to approach the stationary UGVs.
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| 3. |
- Gottwald, Janna M., et al.
(författare)
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Infants prospectively control reaching based on the difficulty of future actions : To what extent can infants' multiple step actions be explained by Fitts' law?
- 2017
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Ingår i: Developmental Psychology. - : American Psychological Association (APA). - 0012-1649 .- 1939-0599. ; 53:1, s. 4-12
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Tidskriftsartikel (refereegranskat)abstract
- Prospective motor control, a key element of action planning, is the ability to adjust one's actions with respect to task demands and action goals in an anticipatory manner. The current study investigates whether 14-month-olds can prospectively control their reaching actions based on the difficulty of the subsequent action. We used a reach-to-place task, with difficulty of the placing action varied by goal size and goal distance. To target prospective motor control, we determined the kinematics of the prior reaching movements using a motion-tracking system. Peak velocity of the first movement unit of the reach served as indicator for prospective motor control. Both difficulty aspects (goal size and goal distance) affected prior reaching, suggesting that both these aspects of the subsequent action have an impact on the prior action. The smaller the goal size and the longer the distance to the goal, the slower infants were in the beginning of their reach toward the object. Additionally, we modeled movement times of both reaching and placing actions using a formulation of Fitts' law (as in heading). The model was significant for placement and reaching movement times. These findings suggest that 14-month-olds can plan their future actions and prospectively control their related movements with respect to future task difficulties.
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