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https://doi.org/10.1109/icuas4...
Conference object . Other literature type . Article . 2020 . Peer-reviewed
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Collision Avoidance of SDRE Controller using Artificial Potential Field Method: Application to Aerial Robotics*

Authors: Nekoo, S. R.; Acosta, J. A.; Ollero, A.;

Collision Avoidance of SDRE Controller using Artificial Potential Field Method: Application to Aerial Robotics*

Abstract

This work presents the problem of collision avoidance of the state-dependent Riccati equation (SDRE) controller using the artificial potential field (APF) method. Two themes were selected to illustrate the importance of the problem, collision avoidance between the end-effectors of serial links manipulators and unmanned aerial vehicles (UAVs), working in a shared workspace. The structure of the SDRE has a good potential to accommodate APF formulation in the weighting matrix of states. The distance between the end-effectors or the center-of-mass (CoM) of UAVs is penalized to autonomously guide the robots in a collision-free trajectory while they are working in a common environment. If the robots get close to each other, the weighting matrix of states increases, which actuates the systems to escape from a possible collision. Several simulation studies were done to investigate the proposed controller and the effect of collision avoidance function. It was found that the higher power of the collision avoidance function handles the threat of the impact better. The distance between robots was considered as an index to assess the performance of the controller which showed successful results in the simulations.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Green