Self-Balancing Two-Wheeled Robot Featuring Intelligent End-to-End Deep Visual-Steering

Li, Chih-Hung G.; Long-ping, Zhou; Chao, Yu‐Hua

doi:10.1109/tmech.2020.3036579

Cited by 16 publications

(4 citation statements)

References 26 publications

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“…However, in the process of manual inspection of electric power information and communication rooms, there are some shortcomings such as time and energy consumption, inspection blind area, and lag. ese problems have caused huge security risks to the machine room as a whole, and more seriously, will a ect the safety and stability of the entire power system [3]. Under this environment, exploring the active compliant control system of an intelligent inspection robot in the power room is conducive to improving the flexibility and intelligence of manual inspection, avoiding the possibility of manual inspection omission, misreading, and misremembering, reducing the labor cost and improving the quality and efficiency of inspection.…”

Section: Introductionmentioning

confidence: 99%

Active Compliance Control System for Intelligent Inspection Robot in Power Room

Guan

Zhang

2022

Journal of Control Science and Engineering

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In order to solve the problems of blind spot and time-consuming and laborious monitoring in manual inspection of power information and communication rooms, a kind of active compliant control system for intelligent inspection robots of power information and communication rooms is proposed. This research includes the noncontact detection method of the inspection robot in the power room based on machine vision; the optimization environment of the power room; the control of the inspection robot through the monitoring system terminal; the automatic visual inspection of the machine through the monitoring network transmission; the display of the monitoring terminal and the use of the calibration of the machine; and the edge detection method of the inspection image. The motion model of the inspection robot in the power room is constructed and the compliant control method of the inspection robot is designed. The experimental results show that the ineffective fluctuation range of torque of each joint is the smallest when the inspection robot is disturbed by obstacles in the process of executing signal change instructions, and the average fluctuation range of robot limbs is 0.65%. Conclusion. Based on the research results of this essay, it is proved that the controllability of power signal lamp change can be optimized separately in the future, and the safety of circuit operation can be improved.

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Section: Introductionmentioning

confidence: 99%

Active Compliance Control System for Intelligent Inspection Robot in Power Room

Guan

Zhang

2022

Journal of Control Science and Engineering

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“…2: Factory floor and cluttered room indoors [49] Factory floor 230 13 [34] Corridor indoors with few obstacles 340 7 [35] Corridor, kitchen and laboratory space 600 2 [36] Cluttered corridor indoors 7000 - [50] Cluttered maze-like indoor environment 4000 7 [51] Room with few obstacles 100 4 [52] Corridor indoors 400 55…”

Section: Approximate Sensors Cost (Gbp)mentioning

confidence: 99%

End-to-End Learning for Visual Navigation of Forest Environments

Niu

Zauner

Tarapore

2023

Forests

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Off-road navigation in forest environments is a challenging problem in field robotics. Rovers are required to infer their traversability over a priori unknown and dynamically changing forest terrain using noisy onboard navigation sensors. The problem is compounded for small-sized rovers, such as that of a swarm. Their size-proportional low-viewpoint affords them a restricted view for navigation, which may be partially occluded by forest vegetation. Hand-crafted features, typically employed for terrain traversability analysis, are often brittle and may fail to discriminate obstacles in varying lighting and weather conditions. We design a low-cost navigation system tailored for small-sized forest rovers using self-learned features. The MobileNet-V1 and MobileNet-V2 models, trained following an end-to-end learning approach, are deployed to steer a mobile platform, with a human-in-the-loop, towards traversable paths while avoiding obstacles. Receiving a 128 × 96 pixel RGB image from a monocular camera as input, the algorithm running on a Raspberry Pi 4, exhibited robustness to motion blur, low lighting, shadows and high-contrast lighting conditions. It was able to successfully navigate a total of over 3 km of real-world forest terrain comprising shrubs, dense bushes, tall grass, fallen branches, fallen tree trunks, and standing trees, in over five different weather conditions and four different times of day.

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“…In recent years, autonomous robots have been invented rapidly to share manpower requirements in factories, restaurants [1], airports [2], and delivery [3] [4]. Unlike conventional robots and human workers operating as separate workspaces, human-robot cooperation is used to complete complex tasks.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy LQR PID Control for a Two-Legged Wheel Robot with Uncertainties and Variant Height

Tran,

Hoang,

Loc

et al. 2023

Journal of Robotics and Control

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This paper proposes a fuzzy LQR PID control for a two-legged wheeled balancing robot for keeping stability against uncertainties and variant heights. The proposed control includes the fuzzy supervisor, LQR, PID, and two calibrations. The fuzzy LQR is conducted to control the stability and motion of the robot while its posture changes with respect to time. The fuzzy supervisor is used to adjust the LQR control according to the robotic height. It consists of one input and one output. The input and output have three membership functions, respectively, to three postures of the robot. The PID control is used to control the posture of the robot. The first calibration is used to compensate for the bias value of the tilting angle when the robot changes its posture. The second calibration is applied to compute the robotic height according to the hip angle. In order to verify the effectiveness of the proposed control, a practical robot with the variant height is constructed, and the proposed control is embedded in the control board. Finally, two experiments are also conducted to verify the balancing and moving ability of the robot with the variant posture.

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Self-Balancing Two-Wheeled Robot Featuring Intelligent End-to-End Deep Visual-Steering

Cited by 16 publications

References 26 publications

Active Compliance Control System for Intelligent Inspection Robot in Power Room

Active Compliance Control System for Intelligent Inspection Robot in Power Room

End-to-End Learning for Visual Navigation of Forest Environments

A Fuzzy LQR PID Control for a Two-Legged Wheel Robot with Uncertainties and Variant Height

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