Wheelchair robot navigation in different weather conditions using deep learning and evolved neural controller

Khalilullah, K. M. Ibrahim; Ota, Shunsuke; Yasuda, Toshiyuki; Jindai, Mitsuru

doi:10.1108/ir-08-2018-0176

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…We believe that one of the significant future scope of this proposed DGT filter will be the autonomous navigation of mobile robot in uneven terrain, simultaneously localization and mapping, drones, optimal 3D mapping and humanoid robotics (Tsai et al , 2014; Bogue, 2017; Khalilullah et al , 2019).…”

Section: Discussionmentioning

confidence: 99%

Optimized 3D laser point cloud reconstruction by gradient descent technique

Singh

Khurana

Kumar

2020

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Purpose This study aims to develop an optimized 3D laser point reconstruction using Descent Gradient algorithm. Precise and accurate reconstruction of 3D laser point cloud of the complex environment/object is a key solution for many industries such as construction, gaming, automobiles, aerial navigation, architecture and automation. A 2D laser scanner along with a servo motor/pan tilt/inertial measurement unit is used for generating 3D point cloud (either environment/object or both) by acquiring the real-time data from sensors. However, while generating the 3D laser point cloud, various problems related to time synchronization problem between laser and servomotor and torque variation in servomotors arise, which causes misalignment in stacking the 2D laser scan for generating the 3D point cloud of the environment. Because of the misalignment in stacking, the 2D laser scan corresponding to the erroneous angular and position information by the servomotor and the 3D laser point cloud become distorted in terms of inconsistency for measuring the dimension of the objects. Design/methodology/approach This paper addresses a modified 3D laser system assembled from a 2D laser scanner coupled with a servomotor (dynamixel motor) for developing an efficient 3D laser point cloud with the implementation of an optimization technique: descent gradient filter (DGT). The proposed approach reduces the cost function (error) in the angular and position coordinates of the servo motor caused because of torque variation and time synchronization, which resulted in enhancing the accuracy in 3D point cloud mapping for the accurate measurement of the object’s dimensions. Findings Various real-world experiments are performed with the proposed DGT filter linked with laser scanner and servomotor and an improvement of 6.5 per cent in measuring the accurate dimension of object is obtained while comparing with conventional approaches for generating a 3D laser point cloud. Originality/value This proposed technique may be applicable for various industrial applications that are based on robotics arms (such as painting, welding and cutting) in the automobile industry, the optimized measurement of object, efficient mobile robot navigation, precise 3D reconstruction of environment/object in construction, architecture applications, airborne applications and aerial navigation.

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Section: Discussionmentioning

confidence: 99%