Comparison of Boosting Based Terrain Classification Using Proprioceptive and Exteroceptive Data

Krebs, Ambroise; Pradalier, CÃ©dric; Siegwart, Roland

doi:10.1007/978-3-642-00196-3_11

Cited by 13 publications

(7 citation statements)

References 8 publications

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“…Motor currents and rate-of-turn of a robot were also correlated with soil parameters (Ojeda, Borenstein, Witus & Karlsen, 2006). Vibrations induced by wheelground interaction were fed to different types of terrain classifiers that discriminate based on, respectively, Mahalanobis distance of the power spectral densities (Brooks & Iagnemma, 2005), AdaBoost (Krebs, Pradalier & Siegwart, 2009), and neural network (Dupont, Moore, Collins & Coyle, 2008).…”

Section: Literature Reviewmentioning

confidence: 99%

“…For example, exteroceptive and proprioceptive features were applied separately showing comparable results but no attempt was made to combine them (Krebs, Pradalier & Siegwart, 2009). A self-supervised learning framework was proposed using a proprioceptive terrain classifier to train an exteroceptive (i.e., vision-based) terrain classifier (Brooks & Iagnemma, 2007).…”

Section: Literature Reviewmentioning

confidence: 99%

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Terrain assessment for precision agriculture using vehicle dynamic modelling

Reina

Milella

Galati

2017

Biosystems Engineering

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Advances in precision agriculture greatly rely on innovative control and sensing technologies that allow service units to increase their level of driving automation while ensuring at the same time high safety standards. This paper deals with automatic terrain estimation and classification that is performed simultaneously by an agricultural vehicle during normal operations.Vehicle mobility and safety, and the successful implementation of important agricultural tasks including seeding, plowing, fertilising and controlled traffic depend or can be improved by a correct identification of the terrain that is traversed. The novelty of this research lies in that terrain estimation is performed by using not only traditional appearance-based features, that is colour and geometric properties, but also contact-based features, that is measuring physics-based dynamic effects that govern the vehicle-terrain interaction and that greatly affect its mobility. Experimental results obtained from an all-terrain vehicle operating on different surfaces are presented to validate the system in the field. It was shown that a terrain classifier trained with contact features was able to achieve a correct prediction rate of 85.1%,

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Terrain assessment for precision agriculture using vehicle dynamic modelling

Reina

Milella

Galati

2017

Biosystems Engineering

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“…After the exploration step we used a simple thresholdbased binary terrain classifier to automatically label the holes in the analyzed areas. Example of more advanced terrain classification can be seen in [31] and [32]. Results using 3 An object generates an occluded area on the VRS (first row).…”

Section: A Experimental Setupmentioning

confidence: 99%

Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces

Caccamo¹,

Bekiroglu²,

Ek³

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Field and Gaussian Process Implicit Surfaces. The system investigates incomplete point clouds in order to find a small set of regions of interest which are then physically explored with a robotic arm equipped with tactile sensors. We show experimental results obtained using a PrimeSense camera, a Kinova Jaco2 robotic arm and Optoforce sensors on different scenarios. We then demonstrate how to use the online framework for object detection and terrain classification.

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“…When it comes to terrain interaction in robotics, most work is done using terrain classification [43]. This involves identifying which out of a few predefined terrain classes a new sample belongs to.…”

Section: Legged Roboticsmentioning

confidence: 99%

Multi-objective evolution of fast and stable gaits on a physical quadruped robotic platform

Nygaard

Tørresen

Glette

2016

2016 IEEE Symposium Series on Computational Intelligence (SSCI)

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Robots are used in increasingly complex environments and need to be able to adapt to changes and unexpected events. This has traditionally been solved by changing the control of a robot, but having an adjustable body can unlock new and powerful adaptive capabilities. An adaptive morphology allows tuning of the physical structure of the robot to different, often conflicting, dynamic requirements, including speed, stability, and efficiency. It can also unlock new functionalities that might not be possible with static morphologies, including variable gearing and multiple locomotion modalities. Even with the potential benefits of morphological adaptation, the methods and technology are still not at a point where there is wide-spread use of adaptive morphologies in physical robots.The main goal of the thesis is to develop methods and technology to enable adaptation of the physical body of a robot to new real-world environments. An evolutionary approach is taken, and to what degree evolutionary algorithms are able to exploit the dynamic morphology of a legged robot is investigated. The feasibility of continuous adaptation of morphology in realistic outdoor environments is also explored.A quadruped mammal-inspired robot with the ability to continuously adjust the length of its legs during operation has been designed and implemented as part of the work outlined in the thesis. Evolutionary algorithms are used to optimize both the control and morphology of the robot to different hardware conditions and walking surfaces in the lab. To achieve this, a new gait controller concept with an adjustable complexity is introduced. This allows evolution in scenarios with a wide range of evaluation budgets. A final proof-of-concept implementation of adaptive morphology is also demonstrated. Our robot was shown to be able to adapt its body continuously while walking in different unstructured outdoor terrains, significantly outperforming a non-adaptive approach.The thesis concludes that adaptation of the physical body of a robot is feasible, and in fact, already shows significant benefits with current technology and methods. Evolutionary algorithms are shown to be effective for adaptation of morphology in a range of different conditions. By developing new methods and technology, as well as demonstrating their utility through real-world experiments, we hope to inspire others to use adaptive morphology on their physical robots.

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Comparison of Boosting Based Terrain Classification Using Proprioceptive and Exteroceptive Data

Cited by 13 publications

References 8 publications

Terrain assessment for precision agriculture using vehicle dynamic modelling

Terrain assessment for precision agriculture using vehicle dynamic modelling

Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces

Multi-objective evolution of fast and stable gaits on a physical quadruped robotic platform

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