Towards Hybrid Gait Obstacle Avoidance for a Six Wheel-Legged Robot with Payload Transportation

Chen, Zhihua; Li, Jiehao; Wang, Junzheng; Wang, Shoukun; Zhao, Jing; Li, Jing

doi:10.1007/s10846-021-01417-y

Cited by 71 publications

(26 citation statements)

References 30 publications

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“…The simulation and experimental results demonstrate that through the use of this control framework, the robot alters its foot trajectory in dynamic, unstructured terrain and achieves an elastic gait for obstacle avoidance. And Chen et al [11] also demonstrated how the realisation of the robot's path planning and wheel-leg obstacle avoidance through terrain inspection is made possible by the application of visual perception system recognition.…”

Section: Related Workmentioning

confidence: 99%

Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment

2023

International Journal of Aerospace Engineering

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The unmanned aerial vehicles (UAV) are now widely used in search and rescue (SAR) missions to locate casualties and survey terrain. To solve the problem of long calculation time and large memory usage of the UAV obstacle-avoidance path-planning algorithm in cooperative tasks, this paper proposes a method that combines the A ∗ algorithm and the task allocation algorithm to achieve a faster and more effective path-planning method. First, the environment is displayed in the form of a grid. Then, the enhanced algorithm divides the task area for UAVs. Finally, each UAV performs SAR path planning in the mission area. The tasks of mapping the environment and searching for target points by UAV swarms are discussed in this study. Our research enhances A ∗ algorithms for generating the shortest collision-free paths for drone swarms. Further, we evaluate the algorithm via simulating the task assignment algorithm and path-planning algorithm of a 3D map and 2D map. Compared with the traditional A ∗ algorithm, the results demonstrate that the enhanced algorithm is effective in the scenario.

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Section: Related Workmentioning

confidence: 99%

Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment

2023

International Journal of Aerospace Engineering

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“…Combining tracks and wheels can also achieve improved locomotion performance [14], [15]. Another way to achieve hybrid locomotion is to mechanically integrate more than one strategy, e.g., wheels attached at the distal tips of individual legs [16], [17], [18], [19], [20]. There are also mechanisms with legs attached to the rims of individual wheels that can be folded or stretched out [21].…”

Section: B Existing Hybrid Locomotion Systemsmentioning

confidence: 99%

$\mathbf{\alpha }$-WaLTR: Adaptive Wheel-and-Leg Transformable Robot for Versatile Multiterrain Locomotion

et al. 2023

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Adaptability is a fundamental yet challenging requirement for mobile robot locomotion. This article presents α-WaLTR, a new adaptive wheel-and-leg transformable robot for versatile multiterrain mobility. The robot has four passively transformable wheels, where each wheel consists of a central gear and multiple leg segments with embedded spring suspension for vibration reduction. These wheels enable the robot to traverse various terrains, obstacles, and stairs while retaining the simplicity in primary control and operation principles of conventional wheeled robots. The chassis dimensions and the center of gravity location were determined by a multiobjective design optimization process aimed at minimizing the weight and maximizing the robot's pitch angle for obstacle climbing. Unity-based simulations guided the selection of the design variables associated with the transformable wheels. Following the design process, α-WaLTR with an embedded sensing and control system was developed. Experiments showed that the spring suspension on the wheels effectively reduced the vibrations when operated in the legged mode and verified that the robot's versatile locomotion capabilities were highly consistent with the simulations. The system-level integration with an embedded control system was demonstrated via autonomous stair detection, navigation, and climbing capabilities.

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“…It generates eye movement event classification from raw eye movement data without any predefined feature extraction or postprocessing steps, reducing the time spent on manual coding. GazeNet’s inspiration refers to a sequence-to-sequence long-short term memory (LSTM) and a hybrid density network (Chen et al , 2021) as the output layer. The overall architecture of the network is a four-layer depth, with a sequence step of 100 seconds and 20 steps – Gaussian mixture component.…”

Section: Application Of Convolutional Neural Network In Eye Control S...mentioning

confidence: 99%

Eye control system based on convolutional neural network: a review

Xiong

Nie

2022

Self Cite

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Purpose This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research. Design/methodology/approach In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated. Findings The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions. Originality/value This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.

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Towards Hybrid Gait Obstacle Avoidance for a Six Wheel-Legged Robot with Payload Transportation

Cited by 71 publications

References 30 publications

Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment

Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment

$\mathbf{\alpha }$-WaLTR: Adaptive Wheel-and-Leg Transformable Robot for Versatile Multiterrain Locomotion

Eye control system based on convolutional neural network: a review

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Towards Hybrid Gait Obstacle Avoidance for a Six Wheel-Legged Robot with Payload Transportation

Cited by 71 publications

References 30 publications

Multi-UAV Search and Rescue with Enhanced A ∗ Algorithm Path Planning in 3D Environment

Multi-UAV Search and Rescue with Enhanced A ∗ Algorithm Path Planning in 3D Environment

$\mathbf{\alpha }$-WaLTR: Adaptive Wheel-and-Leg Transformable Robot for Versatile Multiterrain Locomotion

Eye control system based on convolutional neural network: a review

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Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment

Multi-UAV Search and Rescue with Enhanced A $^{*}$ Algorithm Path Planning in 3D Environment