1P2-S-026 Achievement of an Operation in which a small object is transported by the cooperated operation of two Mobile Robots which differ in size(Cooperation Control of Multi Robot,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)

This paper examines the problem of distributed coverage of an initially unknown environment using a multi-robot system. Specifically, focus is on a coverage technique for coordinating teams of multiple mobile robots that are deployed and maintained in a certain formation while covering the environment. The technique is analyzed theoretically and experimentally to verify its operation and performance within the Webots robot simulator, as well as on physical robots. Experimental results show that the described coverage technique with robot teams moving in formation can perform comparably with a technique where the robots move individually while covering the environment. The authors also quantify the effect of various parameters of the system, such as the size of the robot teams, the presence of localization, and wheel slip noise, as well as environment related features like the size of the environment and the presence of obstacles and walls on the performance of the area coverage operation.

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Edge-weighted consensus-based formation control strategy with collision avoidance

Robotica ◽

10.1017/s0263574714000368 ◽

2014 ◽

Vol 33 (2) ◽

pp. 332-347 ◽

Cited By ~ 32

Author(s):

Riccardo Falconi ◽

Lorenzo Sabattini ◽

Cristian Secchi ◽

Cesare Fantuzzi ◽

Claudio Melchiorri

Keyword(s):

Mobile Robots ◽

Collision Avoidance ◽

Obstacle Avoidance ◽

Control Strategy ◽

Formation Control ◽

Weighted Graphs ◽

Wheeled Robots ◽

Unknown Environments ◽

Multi Robot

SUMMARYIn this paper, a consensus-based control strategy is presented to gather formation for a group of differential-wheeled robots. The formation shape and the avoidance of collisions between robots are obtained by exploiting the properties of weighted graphs. Since mobile robots are supposed to move in unknown environments, the presented approach to multi-robot coordination has been extended in order to include obstacle avoidance. The effectiveness of the proposed control strategy has been demonstrated by means of analytical proofs. Moreover, results of simulations and experiments on real robots are provided for validation purposes.

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Edge Computing for Mobile Robots: Multi-Robot Feature-Based Lidar Odometry with FPGAs

2019 Twelfth International Conference on Mobile Computing and Ubiquitous Network (ICMU) ◽

10.23919/icmu48249.2019.9006646 ◽

2019 ◽

Cited By ~ 5

Author(s):

L. Qingqing ◽

F. Yuhong ◽

J. Pena Queralta ◽

T. N. Gia ◽

H. Tenhunen ◽

...

Keyword(s):

Mobile Robots ◽

Edge Computing ◽

Feature Based ◽

Multi Robot

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Parameter Identification of Spatial–Temporal Varying Processes by a Multi-Robot System in Realistic Diffusion Fields

Robotica ◽

10.1017/s0263574720000788 ◽

2020 ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Wencen Wu ◽

Jie You ◽

Yufei Zhang ◽

Mingchen Li ◽

Kun Su

Keyword(s):

Parameter Identification ◽

Mobile Robots ◽

Sensor Network ◽

Nonlinear Partial Differential Equation ◽

Least Square ◽

Diffusion Field ◽

Recursive Least Square ◽

Robot System ◽

Parameterized Model ◽

Multi Robot

SUMMARY In this article, we investigate the problem of parameter identification of spatial–temporal varying processes described by a general nonlinear partial differential equation and validate the feasibility and robustness of the proposed algorithm using a group of coordinated mobile robots equipped with sensors in a realistic diffusion field. Based on the online parameter identification method developed in our previous work using multiple mobile robots, in this article, we first develop a parameterized model that represents the nonlinear spatially distributed field, then develop a parameter identification scheme consisting of a cooperative Kalman filter and recursive least square method. In the experiments, we focus on the diffusion field and consider the realistic scenarios that the diffusion field contains obstacles and hazard zones that the robots should avoid. The identified parameters together with the located source could potentially assist in the reconstruction and monitoring of the field. To validate the proposed methods, we generate a controllable carbon dioxide (CO2) field in our laboratory and build a static CO2 sensor network to measure and calibrate the field. With the reconstructed realistic diffusion field measured by the sensor network, a multi-robot system is developed to perform the parameter identification in the field. The results of simulations and experiments show satisfactory performance and robustness of the proposed algorithms.

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