An indoor mobile robot navigation technique using odometry and electronic compass

Chen, Weihua; Zhang, Tie

doi:10.1177/1729881417711643

Cited by 27 publications

(16 citation statements)

References 22 publications

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“…with Y 3 , G 3 , q 4 and G 4 as yet to be derived. Upon first substituting equations (4) and (19) into equation (12), and then substituting equations (12) and (18) into equation (13), one obtains…”

Section: Multibody Dynamics Modelmentioning

confidence: 99%

“…Due to their simple and reliable propulsion mechanism, DDMRs are adopted in almost all research fields: pathtracking, [5][6][7][8][9] trajectory-planning, [10][11][12][13][14] position-estimation, 15,16 navigation control [17][18][19] and multi-robot control. [20][21][22] Robot models are the indispensable basis for the various applications mentioned earlier.…”

Section: Introductionmentioning

confidence: 99%

“…Generally speaking, kinematics models are more popular in applications, not only for estimation 15,16 and planning, 11,13,14 but also for control. 8,17,18,20 Most kinematics models involve differential equations due to the nonholonomic constraints of DDMRs, 7,14,15,19,22 while some kinematics models are based on geometric relations that rely on the instantaneous centre of curvature or trajectory approximation at each sampling instant. [16][17][18]20 Besides the robot kinematics, it is important to consider the robot dynamics when highspeed movement and/or heavy-load operations are required in realistic work fields.…”

Section: Introductionmentioning

confidence: 99%

“…8,17,18,20 Most kinematics models involve differential equations due to the nonholonomic constraints of DDMRs, 7,14,15,19,22 while some kinematics models are based on geometric relations that rely on the instantaneous centre of curvature or trajectory approximation at each sampling instant. [16][17][18]20 Besides the robot kinematics, it is important to consider the robot dynamics when highspeed movement and/or heavy-load operations are required in realistic work fields. 23 The dynamics models can associate platform twist with motor armature voltage, 5 or with duty ratio of pulse width modulation of motor voltage, 12 or relate wheel forces to robot acceleration.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Steering-angle computation for the multibody modelling of differential-driving mobile robots with a caster

Ángeles²,

Zou

et al. 2018

International Journal of Advanced Robotic Systems

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Since many off-the-shelf motor drives are supplied with complete control capability in the current, velocity and position loop, the robot model in the navigation control architecture can be oriented either to kinematics, interfaced with the velocity loop, or to dynamics, with the motor-current loop. Moreover, no constraints are imposed by a caster on the mobility of differential-driving mobile robots. Hence, a reduced model, containing only the platform, is sufficient for navigation control based only on the robot kinematics. However, if the multibody system model is used for navigation control based on the robot dynamics, to cope with the demands of high-speed manoeuvres and/or heavy-load operations, then the caster kinematics, especially the knowledge of the steering angle, is required to calculate the inertia matrix and the terms of Coriolis and centrifugal forces. While this angle can be measured by means of dedicated encoders to be installed for casters, the computation technique based on the existing tachometers, already mounted on the motor shafts for the servo control of the two driving wheels, is proved to be sufficient. Both a thorough kinematics model and a multibody dynamics model, including the platform and all different wheels, are formulated here for differential-driving mobile robots. Computational methods based on velocity compatibility and rigid body twists are proposed to estimate the steering angle. Simulation results of the differential-driving mobile robot moving on a smooth trajectory show the feasibility of the steering-angle computational scheme, which obviates the need of installing caster encoders. Moreover, a performance comparison on system modelling is implemented via simulation, between the differential-driving mobile robot model with and without caster dynamics. This further validates the importance of the dynamic effects of casters on the whole system model. Therefore, the multibody modelling approach for casters with the steering-angle computation technique can facilitate the navigation control architecture under dynamics conditions.

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Section: Multibody Dynamics Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Steering-angle computation for the multibody modelling of differential-driving mobile robots with a caster

Ángeles²,

Zou

et al. 2018

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

“…One major challenge of the indoor navigation system is the unavailability of the global position system (GPS) signal in indoor environment. Therefore, many other sensors have been applied in the system such as sonar [3], odometry [4], light detection and ranging (LiDAR) [2], camera [5], and inertial measurement unit (IMU) [6]. With the recent development in vision-based techniques, cameras used as sensors make the vision-based navigation system more and more attractive [7].…”

Section: Introductionmentioning

confidence: 99%

An Indoor Navigation System Based on Stereo Camera and Inertial Sensors with Points and Lines

Yang

Zhang

et al. 2018

Journal of Sensors

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An indoor navigation system based on stereo camera and inertial sensors with points and lines is proposed to further improve the accuracy and robustness of the navigation system in complex indoor environments. The point and line features, which are fast extracted by ORB method and line segment detector (LSD) method, are both employed in this system to improve its ability to adapt to complex environments. In addition, two different representations of lines are adopted to improve the efficiency of the system. Besides stereo camera, an inertial measurement unit (IMU) is also used in the system to further improve its accuracy and robustness. An estimator is designed to integrate the camera and IMU measurements in a tightly coupled approach. The experimental results show that the performance of the proposed navigation system is better than the point-only VINS and the vision-only navigation system with points and lines.

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Implementation of grey wolf optimization controller for multiple humanoid navigation

Muni

Parhi

Kumar

2020

Computer Animation & Virtual

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In this paper, grey wolf optimization controller (GWOC) is considered as a multiobjective technique for multiple humanoid navigations. Upon activation of GWOC, the humanoids mimic the group hunting behavior of grey wolves and navigate toward the target in a collision-free manner in presence of both static and dynamic hurdles. The wolves in the pack will either diverge for searching prey or converge together for attacking the prey following the best search agent (Leader Alpha). GWOC has the ability to keep the humanoid free from being trapped in local minima whereas it facilitates it to head toward global minima. GWOC provides better results as compared to other intelligent techniques because of its five characteristics that include safe boundary, protection, following, hunting, and caring. Both simulation and experimental navigation in laboratory conditions for single as well as for multiple humanoid NAOs have been carried out. From the results of simulation and experimental data, it is confirmed that GWOC provides global minima for humanoid robots in complex environments with different shaped obstacles. A Petri-net controller is considered while navigating multiple humanoids, as during multiple humanoid navigations, one humanoid robot acts as a dynamic obstacle to other humanoids. K E Y W O R D SGWOC, NAO humanoid, navigation, petri-net model INTRODUCTIONLot of research works have been performed for path navigation of mobile robots, biped robots, and industrial robots by using both classical and artificial intelligent techniques. But there is still some improvement needed to avoid the trapping of robots in local minima. Today, the main challenging task for researchers is the path navigation of humanoids having multidegrees of freedom by using computational methods. Though several researchers are working on it, still it is in virtue to obtain the best intelligent method for effective and efficient navigation. For this purpose, grey wolf optimization controller (GWOC) is considered. The humanoid NAO considered for this research work is developed by ALDEBARAN robotics France, which is having 25 degrees of freedom. 1 There are sensors for detecting the obstacles, cameras to take the images of hurdles, motors, actuators, and batteries to perform the predefined tasks. The obstacle distances and shape of the obstacles are detected by inbuilt ultrasonic sensors and camera mount on the head. The programmed GWOC activates when NAO finds any obstacle in its path while heading toward target. Several researchers have worked toward the navigation of different kinds of robots using many intelligent techniques as path navigation of robots plays a Comp Anim Virtual Worlds. 2020;31:e1919. wileyonlinelibrary.com/journal/cav

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An indoor mobile robot navigation technique using odometry and electronic compass

Cited by 27 publications

References 22 publications

Steering-angle computation for the multibody modelling of differential-driving mobile robots with a caster

Steering-angle computation for the multibody modelling of differential-driving mobile robots with a caster

An Indoor Navigation System Based on Stereo Camera and Inertial Sensors with Points and Lines

Implementation of grey wolf optimization controller for multiple humanoid navigation

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