SURF-BRISK–Based Image Infilling Method for Terrain Classification of a Legged Robot

Zhu, Yaguang; Jia, Chaoyu; Ma, Chao; Liu, Qiong

doi:10.3390/app9091779

Cited by 7 publications

(5 citation statements)

References 38 publications

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“…Dante II was also tested on full-scale volcanolike terrain [15], [61], [62]. Some test were conducted along a 170-m path.…”

Section: Testing Methodsmentioning

confidence: 99%

A Review of Mobile Robot Navigation System for Volcano Monitoring Application

Evita¹

2021

ijp

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Volcano is a geological environment including magma, eruption, volcanic edifice and its basements. For continuous monitoring after eruption, a mobile robot could be proposed as an alternative to prevent hazardous effect to volcanologist who perform up close monitoring. In this paper, the robots were divided into 3 types according to their different structures: legged, track-legged and wheeled mobile robots. Meanwhile, the navigation system were implemented in 4 steps suitable for volcano condition: environment mapping, trajectory design, motion control and obstacle avoidance. These navigation system also tested in different locations: indoor, outdoor and real volcano with different testing method for these robots. The testing result was discussed in robot kinematics parameter such as trajectory, velocity, slope angle, rollover and sideslip angels.

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“…Dante II was also tested on full-scale volcanolike terrain [15], [61], [62]. Some test were conducted along a 170-m path.…”

Section: Testing Methodsmentioning

confidence: 99%

A Review of Mobile Robot Navigation System for Volcano Monitoring Application

Evita¹

2021

ijp

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“…Where head v, v ð Þ is the evaluation subfunction of the azimuth angle, dist v, v ð Þ is the evaluation subfunction of the distance between the robot and the obstacle, velo v, v ð Þ is the velocity evaluation subfunction. The values of these three functions are calculated respectively, and then the results are normalized by equations ( 7)- (9).…”

Section: Path Planning Algorithmmentioning

confidence: 99%

“…ORB combines fast corner extraction with brief descriptors, which has the characteristics of fast extraction speed, good robustness to illumination, blur and rotation, but its algorithm accuracy is not high. Authors in Zhu et al 9 proposed a terrain classifier based on the Bow model and SURF-BRISK. The image infilling method was used for identifying terrain with obstacles and mixed terrain.…”

Section: Introductionmentioning

confidence: 99%

Autonomous recognition technology of carrier robot on various terrain environment

Dong

Song²,

Luan³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Field carrier robot can help people carry a certain amount of necessary materials in mountaineering, exploration and other fields, and even help field soldiers carry a certain amount of armaments. However, due to the complexity of the field environment, it is difficult for a robot with a single locomotion mechanism to complete such work. A carrier robot with leg/caterpillar/wheel is proposed. The robot can recognize different terrain environment, so as to select the appropriate locomotion mechanism, and can avoid obstacles and plan the path at the same time. We optimize the traditional ORB algorithm to extract the features of the environment image. The random forest classifier is used to classify the terrain, so as to start the corresponding locomotion mechanism. In addition, the extracted ORB feature points are also used for stereo matching to achieve the depth recovery for environmental information. Based on the analysis of two path planning algorithms of DWA and artificial potential field, an artificial potential field algorithm based on DWA is proposed for robot local path planning. In order to verify the effectiveness of these methods, experiments are carried out on the switching for three locomotion mechanisms and path planning in different practical environments. The results show that when the terrain changes, the robot can effectively switch the locomotion mechanism, and can run stably in different environments.

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“…Zhu et al [2] focus their study on multilegged walking robots. Their redundant limb structure usually confers them good stability and maneuverability even in complex environments.…”

Section: Map Building and Localization Of Mobile Robotsmentioning

confidence: 99%