MONITORING SENSOR OBJECTS USING MOBILE RELAY BY PATH PLANNING FRAMEWORK
DOI:
https://doi.org/10.20894/IJMSR.117.009.001.034Keywords:
Sensor networks, path planning framework.Abstract
The intent of the path planning algorithm is to show the moving or oncoming surface objects. Hence, we apply the optimization of path planning framework algorithm in this work. The algorithmic program shows mobile sensor mechanical phenomenon that are practicable with respect to vehicle dynamics. The objective of the control problem is to less the quality and shows the approximation errors.
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References
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[2] E. Ferre, J. P. Laumond, G. Arechavaleta, C. Esteves, Progresses in path planning, in: International Conference in Product Lifecycle Management, pg. 373-382. (2005).
[3 ]M. Bennewitz, W. Burgard, A probabilistic method for collision-free trajectories of multiple mobile robots. Proc. of the workshop Service Robotics- Applications and Safety Issues in an Emerging Market at the 14th ECAI, (2000).
[4] C.W. Warren, Multiple robotic path coordination using artificial potential fields. In Robotics and Automation. 1990 IEEE International Conference, 01, pg. 500 –505.
[5] R. Ahmad, S. Tichadou, J.Y. Hascoet, 3D Safe and intelligent generation for multi-axis machine tools using vision, International Journal of Computer-Integrated manufacturing, Vol. 25 (4), pg. 365-385, (2012).
[6] L. Zhang, X. Huang, Y. J. Kim, and D. Manocha, D-plan: Efficient collision-free path computation for removal and disassembly. In Journal on Computer-Aided Designs and Applications, (2008).
[7] S. Jun, K. Cha, Y. S. Lee, Optimizing tool orientations, 5-axis machining by configuration-space search method. Computer-Aided Design 35 (6), pg. 549 – 566, (2003).
[8] Z. Liangjun, D. Manocha, An efficient retraction-based RRT planner, in Conference on Robotics and Automation, ICRA, p. 3743-3750, (2008).
[9] J. Pan, S. Chitta, D. Manocha, Faster sample-based motion planning using instance-based learning, Algorithmic Foundations of Robotics X, Springer Berlin Heidelberg, pg. 381-396, (2013).
[10] N. Jetchev, M. Toussaint, Fast motion planning from experience: trajectory prediction for speeding up movement generation, Auton Robot, 34, pg. 111-127, (2013).
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Published
2017-03-27
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