Sensor Information Processing in Robot Competitions and Real World Robotic Challenges

Nagatani, Keiji; Kushleyev, Alex; Lee, Daniel D.

doi:10.1080/01691864.2012.694624

Cited by 10 publications

(1 citation statement)

References 15 publications

(11 reference statements)

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“…MN has robustness against moving objects since localization and control are performed by using only ambient magnetic field. We achieved the long distance run over 1 km as the mission of Tsukuba Challenge 2009 [5]. However, many trial runs and a lot of time ware required.…”

Section: Introductionmentioning

confidence: 99%

Development of magnetic navigation method based on distributed control system using magnetic and geometric landmarks

et al. 2014

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Background:In order for a robot to autonomously run in outdoor environments, a robust and stable navigation method is necessary. Especially, to run in real-world environments, robustness against moving objects is important since many pedestrians and bicycles come and go. Magnetic field, which is not influenced by the moving objects, is considered to be an effective information for autonomous navigation. Methods: Localization technique using a magnetic map, which records ambient magnetic field, has been proposed. The magnetic map is expressed as a linear map. When using this linear magnetic map, swerving from the desired path is a fatal problem. It is because that the magnetic map contains only magnetic data on a desired path. In the paper, we propose a novel navigation method which allows a robot to precisely navigate on a desired path even if localization is performed on the basis of the linear magnetic map. The navigation is performed by using a control method based on a DCS (Distributed Control System). In the system, several navigation modules are executed in parallel, and they independently control the robot by using magnetic and geometric landmarks. Results and discussion: We conducted three navigation experiments. Our robot could perfectly accomplish all navigation even if it was disturbed by many moving objects during the navigation. Conclusions:The control method based on the DCS could switch the navigation module for controlling the robot to cope against the change of its surroundings. The precise and robust navigation was achieved with the proposed method.

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Section: Introductionmentioning

confidence: 99%

Development of magnetic navigation method based on distributed control system using magnetic and geometric landmarks

et al. 2014

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IBA: Intelligent Bug Algorithm – A Novel Strategy to Navigate Mobile Robots Autonomously

Zohaib

Pasha

Javaid

et al. 2014

Communications in Computer and Information Science

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This research proposed an intelligent obstacle avoidance algorithm to navigate an autonomous mobile robot. The presented Intelligent Bug Algorithm (IBA) over performs and reaches the goal in relatively less time as compared to existing Bug algorithms. The improved algorithm offers a goal oriented strategy by following smooth and short trajectory. This has been achieved by continuously considering the goal position during obstacle avoidance. The proposed algorithm is computationally inexpensive and easy to tune. The paper also presents the performance comparison of IBA and reported Bug algorithms. Simulation results of robot navigation in an environment with obstacles demonstrate the performance of the improved algorithm.

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Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle

2014

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Sensor Information Processing in Robot Competitions and Real World Robotic Challenges

Cited by 10 publications

References 15 publications

Development of magnetic navigation method based on distributed control system using magnetic and geometric landmarks

Development of magnetic navigation method based on distributed control system using magnetic and geometric landmarks

IBA: Intelligent Bug Algorithm – A Novel Strategy to Navigate Mobile Robots Autonomously

Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle

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