Development of a control system for a stair-climbing inverted pendulum robot

Wardana, Ananta Adhi; Takaki, Takeshi; Aoyama, Tadayoshi; Ishii, Idaku

doi:10.1109/ica.2016.7811465

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…EnKF is used to eliminate noise measurement of accelerometer sensor and reduce the deviation measurement of a gyro sensor. Feed-Forward controller algorithm used to predict the disturbance in the area of the robot [13].…”

Section: Resultsmentioning

confidence: 99%

Disturbance rejection using feed-forward control system on self balancing robot

Prasetio

Kurniawan

2018

MATEC Web Conf.

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This research implements self-balancing robot using 3 algorithms. There are PID Controller, Ensemble Kalman Filter and Feed-Forward Control system. The PID controller function is as a robot equilibrium control system. The Kalman Ensemble algorithm is used to reduce noise measurement of accelerometer and gyroscope sensors. The PID controller and Ensemble Kalman filter were implemented on self-balancing robot in previous research. In this paper, we added the Feed-Forward controller that serves to detect disturbance derived from the unevenness of the ground. Disturbance is detected using 2 proximity sensors. Base on test results that the system can detect disturbance with an average delay of 2.15 seconds at Kff optimal value is 2.92. Feed-Forward effects result in self-balancing robots increasing power so that the pitch of the robot changes to anticipation of disturbance.

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Section: Resultsmentioning

confidence: 99%

Disturbance rejection using feed-forward control system on self balancing robot

Prasetio

Kurniawan

2018

MATEC Web Conf.

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“…10 Wardana et al developed the control system to adjust the orientations of a wheel-climbing stair robot. 11 The aim is twofold: firstly, the applied torque to the front and rear wheel must be the same, and secondly, the applied torque variation should be minimal along the ground-trackprofile. [12][13][14] The vehicle control element of the UGV involves lateral and longitudinal performances.…”

Section: Introductionmentioning

confidence: 99%

Methodology for the navigation optimization of a terrain-adaptive unmanned ground vehicle

Corral

Alonso

Gómez

et al. 2018

International Journal of Advanced Robotic Systems

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The goal of this article is to design a navigation algorithm to improve the capabilities of an all-terrain unmanned ground vehicle by optimizing its configuration (the angles between its legs and its body) for a given track profile function. The track profile function can be defined either by numerical equations or by points. The angles between the body and the legs can be varied in order to improve the adaptation to the ground profiles. A new dynamic model of an all-terrain vehicle for unstructured environments has been presented. The model is based on a half-vehicle and a quasi-static approach and relates the dynamic variables of interest for navigation with the topology of the mechanism. The algorithm has been created using a simple equation system. This is an advantage over other algorithms with more complex equations which need more time to be calculated. Additionally, it is possible to optimize to any ground-track-profile of any terrain. In order to prove the soundness of the algorithm developed, some results of different applications have been presented.

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A minimalist Stair Climbing Robot (SCR) formed as a leg balancing & climbing Mobile Inverted Pendulum (MIP)

Yang¹,

Bewley²

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Development of a control system for a stair-climbing inverted pendulum robot

Cited by 3 publications

References 9 publications

Disturbance rejection using feed-forward control system on self balancing robot

Disturbance rejection using feed-forward control system on self balancing robot

Methodology for the navigation optimization of a terrain-adaptive unmanned ground vehicle

A minimalist Stair Climbing Robot (SCR) formed as a leg balancing & climbing Mobile Inverted Pendulum (MIP)

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