Kinematics control of wheeled robot based on angular rate sensors

Chen, Diansheng; Bai, Feng; Wu, Lin

doi:10.1109/ramech.2008.4690885

Cited by 3 publications

(4 citation statements)

References 6 publications

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“…In order to make the rovers follow the desired trajectories, we use the basic kinematics of the two-wheeled robot (Ichihara and Ohnishi, 2006;Chen et al, 2008). The rolling and jumping motion working mechanism is shown in Figures 2A,B.…”

Section: Rover's Kinematics and Controlmentioning

confidence: 99%

Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

Jung

Tan

Dai

2022

Front. Control Eng.

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This paper demonstrates an innovative group of robots, consisting of jumping rovers and a charging station, improved traversability and extended energy endurance when traveling to multiple target locations. By employing different jumping rovers with distinct energy consumption characteristics and jumping capabilities, we focus on searching for the most energy-efficient path of each jumping rover in a multi-waypoints visiting mission with obstacles. As jumping rovers can jump onto or over some obstacles without navigating around them, they have the potential to save energy by generating alternative paths to overcome obstacles. Moreover, due to the energy demands for the multi-waypoints mission and the limited battery capacity, a charging station is considered to provide extra energy for enhanced endurance during the mission. We first apply a refined rapidly-exploring random tree star (RRT∗) algorithm to find energy-efficient paths between any two target locations. Then, the genetic algorithm (GA) is applied to select the most profitable combination of paths to visit all targets with energy constraints. Finally, we verify the improved mobility and energy efficiency in both virtual simulation and experimental tests using a group of customized jumping rovers with a charging station and the proposed path planning and task allocation method.

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Section: Rover's Kinematics and Controlmentioning

confidence: 99%

Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

Jung

Tan

Dai

2022

Front. Control Eng.

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“…Thus, the kinematic structure of a generic two-wheeled robot must be understood first. The kinematics of two wheeled robots is well known and is available in the open literature [17][18][19]. In this research, the kinematic structure and analysis is based on the motion variables shown in Figure 2.9.…”

Section: Kinematic Analysismentioning

confidence: 99%

“…There are many discussions in the literature to address these difficulties [17][18][19][20][21]. This research utilized two different control methods, which will be discussed in the following sections, to address this difficulty.…”

Section: Control Algorithmmentioning

confidence: 99%

Analysis and Design of a Two-Wheeled Robot With Multiple User Interface Inputs and Vision Feedback Control

Olson

Rizwan

Shiakolas

et al. 2012

Volume 4: Dynamics, Control and Uncertainty, Parts a and B

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Environments for robotics research and education are usually based on open source code or use proprietary software tools. Open source usually requires a user to know a low level programming language and proprietary software does not provide the environment needed for research and educational activities. In addition to the software, the hardware must be inexpensively and easily fabricated and assembled for teaching and experimentation purposes. In this manuscript, we will present the design and fabrication of a small size two-wheel mobile robotic platform developed for research and education purposes. Subsequently, the software environment for controlling the robot which is based on LabVIEW will be presented. LabVIEW was chosen because it provides many built-in toolboxes, and it is characterized by expandability and ease of interface with external devices. The software allows experienced as well as novice users to develop control code with ease. The robot communicates with control software in LabVIEW through a Bluetooth device. The developed environment is used to control the robot through multiple interfaces, to implement obstacle avoidance algorithms with ease, to implement open and closed loop control algorithms, to easily incorporate and use an inexpensive web camera for vision calibration, and is currently used to implement image processing and voice processing algorithms for robot localization and control both for research and education in both undergraduate and graduate courses.

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“…Other sensors, like gyroscopes, can be used in order to complement odometric information and improve accuracy. As examples, in [ 15 ], the information of the odometric system is fused with gyro information according to a set of rules; In [ 16 ], the rate angle is measurement using a gyroscope and the displacement using only one encoder; In [ 17 ], the authors intend to correct odometry errors when the robot is traversing a bump, trying to reduce non-systematic errors and getting robot angle in the bump based only on gyro information. In [ 18 ], an Unscented Kalman filter is used to fuse information from odometry and gyroscope, improving final accuracy.…”

Section: Introductionmentioning

confidence: 99%

Improving Odometric Accuracy for an Autonomous Electric Cart

Toledo

Piñeiro

Arnay

et al. 2018

Sensors

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In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

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Kinematics control of wheeled robot based on angular rate sensors

Cited by 3 publications

References 6 publications

Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

Analysis and Design of a Two-Wheeled Robot With Multiple User Interface Inputs and Vision Feedback Control

Improving Odometric Accuracy for an Autonomous Electric Cart

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