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Noise, morphology and control. An analysis of the stochastic behaviour of Braitenberg vehicles.

Rano, Ignacio (2015) Noise, morphology and control. An analysis of the stochastic behaviour of Braitenberg vehicles. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015, Hamburg, Germany. IEEE/RSJ. 6 pp. [Conference contribution]

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Braitenberg vehicles are simple models of the motion of animal towards, or away from, a stimulus. They have been used to implement target reaching and avoidance behaviours in robotics, based, among others, on sound, light, distance, and pressure sensors. When the sensors are accurate enough -- when they provide a high signal to noise ratio -- variations on the readings can be neglected. Their behaviour, in these applications, can be explained using a non-linear deterministic dynamical system. For noisy sensors, or when the physical interaction between the robot and the measured variable is complex, a deterministic model is not good enough. Some examples include robots with cheap sensors, sensor prototypes, or settings where the interaction with the environment changes the measurements, like odour tracking -- as the motion of the robot creates turbulences in the air. This paper presents the first analysis of the behaviour of Braitenberg vehicle 3a with noisy sensors. The mathematical equations of the evolution of the vehicle state probability are derived under white noise assumptions, and a bound for the vehicle state uncertainty is obtained assuming Gaussian probability distributions of the pose. These equations relate the morphological parameters of the vehicle, the noise variance and the function connecting the sensors to the actuators. The non-linear controller simulations illustrate the local validity of the model, and global simulations show how the vehicles converge.

Item Type:Conference contribution (Paper)
Keywords:Mobile robotics
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:32113
Deposited By: Dr Ignacio Rano
Deposited On:22 Jun 2016 10:03
Last Modified:17 Oct 2017 16:19

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