ICUAS 2020 Paper Abstract

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Paper WePS.8

Nekoo, Saeed Rafee (Escuela Técnica Superior de Ingeniería, Universidad de Sevilla), Acosta, Jose Angel (Universidad de Sevilla), Ollero, Anibal (Universidad de Sevilla)

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

Scheduled for presentation during the Poster Session "Poster Papers Session" (WePS), Wednesday, September 2, 2020, 13:00−18:00, Foyer, Mezzanine Level

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on April 24, 2024

Keywords Simulation, Navigation, Path Planning

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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