A Distributed Self-Deployment Algorithm Suitable for Multiple Nonholonomic Mobile Robots

2008 ◽  
Author(s):  
Yu Zhou
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Variational Calculus ◽  
Dissipation Function ◽  
Nonholonomic Mobile Robots ◽  
Local Configuration ◽  
Robot Systems ◽  
The Difference ◽  
The Stability ◽  
Multi Robot

This paper introduces a novel distributed algorithm for deploying multi-robot systems, consisting of mobile robots with onboard sensing and wireless communication of limited ranges, to approach the desired sensory coverage while maintaining communication connection over targeted 2D environments. A virtual potential energy is defined for each mobile robot according to the difference between the actual and desired configurations in the neighborhood of the robot, which generates the actuating force to move the robot towards the desired local coverage. The Rayleigh’s dissipation function is adopted to provide the necessary damping mechanism which maintains the stability of the deployment motion for each robot. The equation of deployment motion for each mobile robot is then derived from the Hamilton’s principle using the method of the variational calculus, which defines the movement of the robot to approach the desired local configuration. The formulation of the variational calculus also provides a convenience way to incorporate the nonholonomic constraint arising in wheeled robots. Since the equation of deployment motion for each robot depends on only the robot’s own kinematic state and its detectable positional relationship with nearby objects, the proposed algorithm decentralizes the multi-robot deployment problem into the motion control of individual robots. Simulation results show the feasibility of the proposed approach in guiding the deployment of multi-robot systems.

Linear Visual Servoing-Based Control of the Position and Attitude of Omnidirectional Mobile Robots

2011 ◽  
Vol 5 (4) ◽  
pp. 569-574
Author(s):  
Atsushi Ozato ◽  
◽  
Noriaki Maru ◽  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Visual Servoing ◽  
Rotational Velocity ◽  
Target Position ◽  
Visual Space ◽  
Translational Velocity ◽  
Omnidirectional Mobile Robot ◽  
Camera Angle ◽  
The Difference

This article proposes a Linear Visual Servoing (LVS)-based method of controlling the position and attitude of omnidirectional mobile robots. This article uses two markers to express their target position and attitude in binocular visual space coordinates, based on which new binocular visual space information which includes position and attitude angle information is defined. Binocular visual space information and the motion space of an omnidirectional mobile robot are linearly approximated, and, using the approximation matrix and the difference in the binocular visual space information between a target marker and a robot marker, the robot’s translational velocity and rotational velocity are generated. Since those are all generated based only on disparity information on an image, which is similar to how this is done in existing LVS, a camera angle is not required. Thus, the method is robust against calibration errors in camera angles, as is existing LVS. The effectiveness of the proposed method is confirmed by simulation.

scholarly journals Consensus Algorithms Based Multi-Robot Formation Control under Noise and Time Delay Conditions

2019 ◽  
Vol 9 (5) ◽  
pp. 1004 ◽  
Author(s):  
Heng Wei ◽  
Qiang Lv ◽  
Nanxun Duo ◽  
GuoSheng Wang ◽  
Bing Liang
Keyword(s):  
Time Delay ◽  
Mobile Robot ◽  
Formation Control ◽  
Second Order ◽  
Multiple Time ◽  
Consensus Problem ◽  
Robot System ◽  
Maximum Time ◽  
Robot Systems ◽  
Multi Robot

In recent years, the formation control of multi-mobile robots has been widely investigated by researchers. With increasing numbers of robots in the formation, distributed formation control has become the development trend of multi-mobile robot formation control, and the consensus problem is the most basic problem in the distributed multi-mobile robot control algorithm. Therefore, it is very important to analyze the consensus of multi-mobile robot systems. There are already mature and sophisticated strategies solving the consensus problem in ideal environments. However, in practical applications, uncertain factors like communication noise, communication delay and measurement errors will still lead to many problems in multi-robot formation control. In this paper, the consensus problem of second-order multi-robot systems with multiple time delays and noises is analyzed. The characteristic equation of the system is transformed into a quadratic polynomial of pure imaginary eigenvalues using the frequency domain analysis method, and then the critical stability state of the maximum time delay under noisy conditions is obtained. When all robot delays are less than the maximum time delay, the system can be stabilized and achieve consensus. Compared with the traditional Lyapunov method, this algorithm has lower conservativeness, and it is easier to extend the results to higher-order multi-robot systems. Finally, the results are verified by numerical simulation using MATLAB/Simulink. At the same time, a multi-mobile robot platform is built, and the proposed algorithm is applied to an actual multi-robot system. The experimental results show that the proposed algorithm is finally able to achieve the consensus of the second-order multi-robot system under delay and noise interference.

Distributed coverage with mobile robots on a graph: locational optimization and equal-mass partitioning

Robotica ◽  
2013 ◽  
Vol 32 (2) ◽  
pp. 257-277 ◽  
Author(s):  
Seung-kook Yun ◽  
Daniela Rus
Keyword(s):  
Mobile Robots ◽  
Environmental Modeling ◽  
Equal Mass ◽  
Optimal Configuration ◽  
Cost Functions ◽  
Decentralized Algorithms ◽  
Robot Systems ◽  
Multi Robot

SUMMARYThis paper presents decentralized algorithms for coverage with mobile robots on a graph. Coverage is an important capability of multi-robot systems engaged in a number of different applications, including placement for environmental modeling, deployment for maximal quality surveillance, and even coordinated construction. We use distributed vertex substitution for locational optimization and equal mass partitioning, and the controllers minimize the corresponding cost functions. We prove that the proposed controller with two-hop communication guarantees convergence to the locally optimal configuration. We evaluate the algorithms in simulations and also using four mobile robots.

Neural Control System for Autonomous Vehicles

2011 ◽  
pp. 1197-1204
Author(s):  
Francisco García-Córdova ◽  
Antonio Guerrero-González ◽  
Fulgencio Marín-García
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Neural Control ◽  
Learning Rule ◽  
Nonholonomic Mobile Robots ◽  
Neural Architecture ◽  
Neuro Controller

Neural networks have been used in a number of robotic applications (Das & Kar, 2006; Fierro & Lewis, 1998), including both manipulators and mobile robots. A typical approach is to use neural networks for nonlinear system modelling, including for instance the learning of forward and inverse models of a plant, noise cancellation, and other forms of nonlinear control (Fierro & Lewis, 1998). An alternative approach is to solve a particular problem by designing a specialized neural network architecture and/or learning rule (Sutton & Barto, 1981). It is clear that biological brains, though exhibiting a certain degree of homogeneity, rely on many specialized circuits designed to solve particular problems. We are interested in understanding how animals are able to solve complex problems such as learning to navigate in an unknown environment, with the aim of applying what is learned of biology to the control of robots (Chang & Gaudiano, 1998; Martínez-Marín, 2007; Montes-González, Santos-Reyes & Ríos- Figueroa, 2006). In particular, this article presents a neural architecture that makes possible the integration of a kinematical adaptive neuro-controller for trajectory tracking and an obstacle avoidance adaptive neuro-controller for nonholonomic mobile robots. The kinematical adaptive neuro-controller is a real-time, unsupervised neural network that learns to control a nonholonomic mobile robot in a nonstationary environment, which is termed Self-Organization Direction Mapping Network (SODMN), and combines associative learning and Vector Associative Map (VAM) learning to generate transformations between spatial and velocity coordinates (García-Córdova, Guerrero-González & García-Marín, 2007). The transformations are learned in an unsupervised training phase, during which the robot moves as a result of randomly selected wheel velocities. The obstacle avoidance adaptive neurocontroller is a neural network that learns to control avoidance behaviours in a mobile robot based on a form of animal learning known as operant conditioning. Learning, which requires no supervision, takes place as the robot moves around a cluttered environment with obstacles. The neural network requires no knowledge of the geometry of the robot or of the quality, number, or configuration of the robot’s sensors. The efficacy of the proposed neural architecture is tested experimentally by a differentially driven mobile robot.

PD-like controller with impedance for delayed bilateral teleoperation of mobile robots

Robotica ◽  
2015 ◽  
Vol 34 (9) ◽  
pp. 2151-2161 ◽  
Author(s):  
E. Slawiñski ◽  
S. García ◽  
L. Salinas ◽  
V. Mut
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Force Feedback ◽  
Robot Motion ◽  
Time Varying ◽  
Control Parameters ◽  
Bilateral Teleoperation ◽  
Teleoperation System ◽  
Control Scheme ◽  
The Stability

SUMMARYThis paper proposes a control scheme applied to the delayed bilateral teleoperation of mobile robots with force feedback in face of asymmetric and time-varying delays. The scheme is managed by a velocity PD-like control plus impedance and a force feedback based on damping and synchronization error. A fictitious force, depending on the robot motion and its environment, is used to avoid possible collisions. In addition, the stability of the system is analyzed from which simple conditions for the control parameters are established in order to assure stability. Finally, the performance of the delayed teleoperation system is shown through experiments where a human operator drives a mobile robot.

Decentralized Multi-Robot Teams Using Wheeled Manipulation for Object Transportation

2012 ◽  
Author(s):  
Tyson L. Ringold ◽  
Raymond J. Cipra
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Dynamic Simulation ◽  
Carrying Capacity ◽  
Arbitrary Number ◽  
Object Interaction ◽  
Wheeled Robot ◽  
Simulation Results ◽  
Object Transportation ◽  
Multi Robot

Object transportation is an especially suitable task for cooperative mobile robots where the carrying capacity of an individual robot is naturally limited. In this work, a unique wheeled robot is presented that, when used in homogeneous teams, is able to lift and carry objects which may be significantly larger than the robot itself. A key feature of the presented robot is that it is devoid of articulated manipulation mechanisms, but instead relies on its drive wheels for object interaction. After a brief introduction to the mechanics of this mobile robot, a behavior-based lifting and carrying strategy is developed that allows the robot to cooperatively raise an object from the ground, transition into a carrying role, and then transport the object across cluttered, unstructured terrain. The strategy is inherently decentralized, allowing an arbitrary number of robots to participate in the transportation task. Dynamic simulation results are then presented, showing the effectiveness of the strategy.

scholarly journals Approximation of Jacobian inverse kinematics algorithms

2009 ◽  
Vol 19 (4) ◽  
pp. 519-531 ◽  
Author(s):  
Krzysztof Tchoń ◽  
Joanna Karpińska ◽  
Mariusz Janiak
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Inverse Kinematics ◽  
Variational Calculus ◽  
Approximation Problem ◽  
The Other ◽  
Synthesis Problem ◽  
Theoretical Concepts ◽  
Jacobian Inverse

Approximation of Jacobian inverse kinematics algorithmsThis paper addresses the synthesis problem of Jacobian inverse kinematics algorithms for stationary manipulators and mobile robots. Special attention is paid to the design of extended Jacobian algorithms that approximate the Jacobian pseudoinverse algorithm. Two approaches to the approximation problem are developed: one relies on variational calculus, the other is differential geometric. Example designs of the extended Jacobian inverse kinematics algorithm for 3DOF manipulators as well as for the unicycle mobile robot illustrate the theoretical concepts.

scholarly journals The Mobile Robot Control in Obstacle Avoidance Using Fuzzy Logic Controller

2020 ◽  
Vol 5 (3) ◽  
pp. 334-351
Author(s):  
M. Khairudin ◽  
R. Refalda ◽  
S. Yatmono ◽  
H. S. Pramono ◽  
A. K. Triatmaja ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Experimental Work ◽  
Fuzzy Logic Controller ◽  
Input Voltage ◽  
Robot System ◽  
Dc Motors ◽  
Robot Systems

A very challenging problem in mobile robot systems is mostly in obstacle avoidance strategies. This study aims to describe how the obstacle avoidance system on mobile robots works. This system is designed automatically using fuzzy logic control (FLC) developed using Matlab to help the mobile robots to avoid a head-on collision. The FLC designs were simulated on the mobile robot system. The simulation was conducted by comparing FLC performance to the proportional integral derivative (PID) controller. The simulation results indicate that FLC works better with lower settling time performance. To validate the results, FLC was used in a mobile robot system. It shows that FLC can control the velocity by braking or accelerating according to the sensor input installed in front of the mobile robot. The FLC control system functions as ultrasonic sensor input or a distance sensor. The input voltage was simulated with the potentiometer, whereas the output was shown by the velocity of DC motor. This study employed the simulation work in Simulink and Matlab, while the experimental work used laboratory scale of mobile robots. The results show that the velocity control of DC motors with FLC produces accurate data, so the robot could avoid the existing obstacles. The findings indicate that the simulation and the experimental work of FLC for mobile robot in obstacle avoidance are very close.

scholarly journals Motion Planning of Multiple Mobile Robots Using Virtual Impedance

1996 ◽  
Vol 8 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Tamio Arai ◽  
◽  
Jun Ota
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Lower Layer ◽  
Local Equilibrium ◽  
Current Position ◽  
Cooperative Motion ◽  
Robot Systems ◽  
Simulation Results ◽  
Virtual Impedance

This paper proposes a planning method for multiple mobile robot systems. It has two characteristics: (1) Each robot plans a path on its own, without any supervisor; (2) The concept of cooperative motion can be implemented. A two-layered hierarchy is defined for a scheme of individual path planning. The higher layer generates a trajectory from the current position to a goal. The lower layer called“Virtual Impedance Metho” makes a real-time plan to follow the generated trajectory while avoiding obstacles and avoiding or cooperating with other robots. This layer is composed of four modules called, “watchdog”, “deadlock solver”,“blockade solver”, and “pilot”. The local equilibrium is detected by the watchdog and cancelled by the deadlock solver or the blockade solver. Simulation results indicate the effectiveness of the proposed method.

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