Towards Fault-Tolerant and Energy-Efficient Swarms of Underwater Robots

Amory, Ammar; Meyer, Benjamin; Osterloh, Christoph; Tosik, Thomas; Maehle, Erik

doi:10.1109/ipdpsw.2013.215

Cited by 13 publications

(2 citation statements)

References 6 publications

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“…In contrast to that, there is also the trend for cheaper, smaller and durable AUVs for e.g. swarm operations [10]. Such AUVs, so called low-cost and low-power AUVs, are focussed in this work.…”

Section: B Related Workmentioning

confidence: 99%

Enhanced State Estimation Based on Particle Filter and Sensor Data With Non-Gaussian and Multimodal Noise

Cimiega

Badri-Hoeher

2021

IEEE Access

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This paper presents a novel approach to state estimation based on particle filter dealing with measurement data effected by non-Gaussian, multimodal noise. The implementation focusses on autonomous underwater vehicles (AUVs) utilizing data of a magnetic compass and a mechanical scanning sonar for spatial navigation. Nowadays, particle filter approaches often require complicated feature extraction methods culminating in semantic interpretation of the data. This is not suitable for low-cost and low-weight AUVs, because these steps require high computational power. Therefore, efficient CPUs and higher power delivery are required. To test the novel approach, the algorithm is simulated in different scenarios with different parameters. Additionally, the filter is applied to real environment data. Finally, the performance is tested and evaluated by several methods. We demonstrate the computational efficiency and superiority of our method over other approaches through simulations.

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Section: B Related Workmentioning

confidence: 99%

Enhanced State Estimation Based on Particle Filter and Sensor Data With Non-Gaussian and Multimodal Noise

Cimiega

Badri-Hoeher

2021

IEEE Access

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“…Yet, the acquirement cost for a commercially available AUV model, as well as its operational cost, especially when the last includes the support of crewed surface vessels, remains high. In recent years there have been efforts to limit AUVs logistics to more affordable levels leading to a significant increase in the capability of small class AUVs with advances in navigation, propulsion, control and compact sonar payloads [9]. A range of oceanographic and geophysical survey instruments can be found on such AUVs, including bathymetric mapping sonars, side-scans and optical cameras, offering a satisfactory quality, covering current engineering and geophysics requirements in a wide range of survey tasks [82].…”

Section: Low Logistics Auvsmentioning

confidence: 99%

Autonomous underwater robots’ cooperative behaviour

Savas¹

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A novel cooperative controller design for autonomous underwater vehicles is proposed, implemented and tested. The design procedure follows the basic principles of behaviourbased systems to create two different biomimetic roles, encapsulating the characteristics of an extremely rare cooperative underwater predator behaviour found in the wild: bottlenose dolphins group-hunting with division of labour and role specialization. The behaviour-based model is comprised of an hierarchy with different levels of competence, interaction and intercommunication between several behaviour modules. Two distinct, cooperating roles mimicking the driver and the non-driving or barrier members of a hunting bottlenose dolphins group emerged from the behaviour-based subsumption architecture controller designation. This behaviour-based cooperation exploits the driver's individual capability, in fact a physical gift, of initializing, coordinating a hunting bout, detecting and herding the school of fish along with the contribution of non-driving dolphins ability to comprehend and follow the driver's master plan and thus act as barriers for the fish trying to escape. Both roles are programmed to act upon sensory information regarding the robot's environment, provided by a vision sensor module and an inertial measurement unit. The vision sensor detects colour light targets, classifies them according to the experimentation scenario and triggers behaviours' interaction. The inertial measurement unit supports behaviours' navigation and guidance necessities. Controller testing, under several simulated scenarios, proved the reliability and modular functionality of the cooperative behaviour-based model and its potential for supporting the autonomy of underwater robotic vessels commissioned in oceanography, environmental monitoring and exploration, serving tasks that can easily be seen as an extent of dolphins' group hunting. Apart from the simulation, the same behaviour-based controller was tested in real world, with a prototype autonomous vessel. In this case, due to certain limitations of the experimental apparatus, the behaviour-based controller implemented an individual biomimetic role inspired by the real life routines of wandering, hunting, feeding, hiding and nesting exercised by underwater creatures. The individual role, behaviour-based controller was an effort to approach the sea creatures' autonomy, observed macroscopically as an inevitable iteration and commutation of distinct behaviour modules, guided by the overall objective of staying alive. The prototype robot was commissioned as an experimentation platform for testing the framework of autonomous behaviour-based controllers and materialize the biomimetic metaphor between the maritime environment and a laboratory experimentation area of 1m 3 .

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Triangle Formation Based Multiple Targets Search Using a Swarm of Robots

Tan

2016

Lecture Notes in Computer Science

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Towards Fault-Tolerant and Energy-Efficient Swarms of Underwater Robots

Cited by 13 publications

References 6 publications

Enhanced State Estimation Based on Particle Filter and Sensor Data With Non-Gaussian and Multimodal Noise

Enhanced State Estimation Based on Particle Filter and Sensor Data With Non-Gaussian and Multimodal Noise

Autonomous underwater robots’ cooperative behaviour

Triangle Formation Based Multiple Targets Search Using a Swarm of Robots

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