N. S. V. Rao, S. S. Iyengar, J. B. Oommen, and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. IEEE J. of Robot. & Autom., 4:450--455, 1988. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Sensor Placement for Effective Coverage and Surveillance.. - Dhillon, Chakrabarty (2003) (1 citation) (Correct)
....the application of our approach. As sensors are used in greater numbers for field operation, efficient deployment strategies become increasingly important. Related work on terrain model acquisition for motion planning has focused on the movement of a robot in an unexplored sensor field [1]. While knowledge of the terrain is vital for surveillance, it does not directly solve the sensor placement problem. Self deployment for mobile sensors based on the notion of potential fields is presented in [8] However, selfdeployment does not provide a solution for case of static sensors that ....
N. S. V. Rao, S. S. Iyengar, B. J. Oomen and R. L. Kashyap, "On terrain model acquisition by a point robot amidst polyhedral obstacles", IEEE Journal of Robotics and Automation, vol. 4, pp. 450-455, August 1988.
A Game-Theoretic Framework For Robot Motion Planning - LaValle (1995) (9 citations) (Correct)
....uncertainty, incomplete or imperfect information is utilized by the robot to make an inference about its environment. With a nondeterministic uncertainty model, the robot might have sufficient information to infer that the environment e belongs to some subset F ae E. For example, in [140] [155], the environment is restricted to a plane populated with unknown polygonal obstacles, which are then discovered using visual scans to build a visibility graph for motion planning. In [127] unknown obstacles are allowed to be of arbitrary shape, and the sensor data consists of tactile ....
N. S. V. Rao, S. S. Iyengar, J. B. Oommen, and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. IEEE J. of Robot. & Autom., 4:450--455, 1988.
On Motion Planning in Changing, Partially-Predictable.. - LaValle, Sharma (1997) (2 citations) (Correct)
....ES uncertainty, incomplete or imperfect information is utilized by the robot to make an inference about its environment. With a nondeterministic uncertainty model, the robot might have sufficient information to infer that the environment e belongs to some subset F ae E. For example, in [50] [53], the environment is restricted to a plane populated with unknown polygonal obstacles, which are then discovered using visual scans to build a visibility graph for motion planning. In [44] unknown obstacles are allowed to be of arbitrary shape, and the sensor data consists of tactile ....
N. S. V. Rao, S. S. Iyengar, J. B. Oommen, and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. IEEE J. of Robot. & Autom., 4:450--455, 1988. 48
Geometric Shortest Paths and Network Optimization - Mitchell (1998) (39 citations) (Correct)
....to a type of relative neighborhood graph in the presence of obstacles. See also [233] For other related work, without theoretical guarantees on the competitive ratio, but useful in autonomous vehicle navigation, we refer the reader to the book edited by Iyengar and Elfes [225] as well as [226, 281, 293, 330, 331]. Mitchell [281] has considered a model, based on a special case of the weighted region problem (Section 4.3) in which the robot gathers information, which it accumulates in a map, and at each step applies the best possible local strategy, assuming travel within known free space has a ....
N. S. V. Rao, S. S. Iyengar, B. J. Oommen, and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. Internat. J. Robot. Autom., 4(4):450--455, 1988.
Grid Coverage for Surveillance and Target Location in.. - Chakrabarty, Iyengar, .. (2002) (19 citations) Self-citation (Iyengar) (Correct)
No context found.
N.S.V. Rao, S.S. Iyengar, B.J. Oomen, and R.L. Kashyap, "On Terrain Model Acquisition by a Point Robot Amidst Polyhedral Obstacles," IEEE J. Robotics and Automation, vol. 4, pp. 450-455, Aug. 1988.
Grid Coverage for Surveillance and Target Location in.. - Chakrabarty, Iyengar, .. (2002) (19 citations) Self-citation (Iyengar) (Correct)
No context found.
N. S. V. Rao, S. S. Iyengar, B. J. Oomen and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. IEEE Journal of Robotics and Automation, vol. 4, pp. 450-455, August 1988.
Sensor Placement for Grid Coverage under Imprecise.. - Dhillon, Chakrabarty.. (2002) (8 citations) Self-citation (Iyengar) (Correct)
....given sensor field architecture. However, as sensors are used in greater numbers for field operation, efficient deployment strategies become increasingly important. Related work on terrain model acquisition for motion planning has focused on the movement of a robot in an unexplored sensor field [5]. While knowledge of the terrain is vital for surveillance, it does not directly solve the sensor placement problem. Self deployment for mobile sensors based on the notion of potential fields has been presented in [13] The fields are constructed such that each sensor is repelled by both ....
N. S. V. Rao, S. S. Iyengar, B. J. Oomen and R. L. Kashyap, On terrain model acquisition by a point robot amidst polyhedral obstacles, IEEE Journal of Robotics and Automation, vol. 4, pp. 450-455, August 1988.
Planning Algorithms - LaValle (2004) (3 citations) (Correct)
No context found.
N. S. V. Rao, S. S. Iyengar, J. B. Oommen, and R. L. Kashyap. On terrain model acquisition by a point robot amidst polyhedral obstacles. IEEE J. of Robot. & Autom., 4:450--455, 1988.
Uncertainty-Aware Sensor Deployment Algorithms for.. - Zou, Chakrabarty (2003) (Correct)
No context found.
N. S. V. Rao, S. S. Iyengar, B. J. Oomen and R. L. Kashyap, "On terrain model acquisition by a point robot amidst polyhedral obstacles", IEEE Journal of Robotics and Automation, vol. 4, pp. 450-455, August 1988.
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