Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.


2014 ◽  
Vol 47 (3) ◽  
pp. 5703-5708 ◽  
Author(s):  
Tiago P. Nascimento ◽  
Andre G.S. Conceicao ◽  
António Paulo Moreira

2019 ◽  
Vol 9 (5) ◽  
pp. 1004 ◽  
Author(s):  
Heng Wei ◽  
Qiang Lv ◽  
Nanxun Duo ◽  
GuoSheng Wang ◽  
Bing Liang

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.


Robotica ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 549-567 ◽  
Author(s):  
Tiago P. Nascimento ◽  
André G. S. Conceição ◽  
António Paulo Moreira

SUMMARYThis paper discusses about a proposed solution to the obstacle avoidance problem in multi-robot systems when applied to active target tracking. It is explained how a nonlinear model predictive formation control (NMPFC) previously proposed solves this problem of fixed and moving obstacle avoidance. First, an approach is presented which uses potential functions as terms of the NMPFC. These terms penalize the proximity with mates and obstacles. A strategy to avoid singularity problems with the potential functions using a modified A* path planning algorithm was then introduced. Results with simulations and experiments with real robots are presented and discussed demonstrating the efficiency of the proposed approach.


Author(s):  
Xuefeng Dai ◽  
Jiazhi Wang ◽  
Dahui Li ◽  
Yanchun Wang

Multi-robot systems have many potential applications; however, the available results for coordination were based on qualitative information. Fuzzy logic reasoning has a feature of human being thinking, so a novel coordinated algorithm is proposed. The algorithm utilizes sharing sensing information of rooms and semantic robots to coordinating robots in a structured environment exploration. The approach divides all teammate robots into two classes according to robot exploration performance, and divides rooms into large, medium and small ones according to estimations of the individual areas. On the purpose of minimizing exploration time of the system, the reasoning coordination assigns large room to good performance robot, and vice versa. A parameter update law is introduced for fuzzy membership functions. Finally, the results are validated by computer simulations for a structured environment.


Author(s):  
Ayman. El shenawy ◽  
Khalil. Mohamed ◽  
Hany. M. Harb

Environment Exploration is the basic process that most of Multi Robot Systems applications depend on it. The exploration process performance depends on the coordination strategy between the robots participating in the team.  In this paper the coordination of Multi Robot Systems in the exploration process is surveyed, and the performance of different Multi Robot Systems exploration strategies is contrasted and analyzed for different environments and different team sizes.


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