Ethologically inspired reactive exploration of coral reefs with collision avoidance: Bridging the gap between human and robot spatial understanding of unstructured environments

Maldonado-Ramírez, Alejandro; Torres-Méndez, L. Abril; Rodriguez-Telles, Francisco

doi:10.1109/iros.2015.7354062

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…The integrated camera enables more autonomous surveying capabilities (73). Monocular self-localization would enable the fish to build maps of the underwater environment and explore it further.…”

Section: Limitations and Future Stepsmentioning

confidence: 99%

Exploration of underwater life with an acoustically controlled soft robotic fish

et al. 2018

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Closeup exploration of underwater life requires new forms of interaction, using biomimetic creatures that are capable of agile swimming maneuvers, equipped with cameras, and supported by remote human operation. Current robotic prototypes do not provide adequate platforms for studying marine life in their natural habitats. This work presents the design, fabrication, control, and oceanic testing of a soft robotic fish that can swim in three dimensions to continuously record the aquatic life it is following or engaging. Using a miniaturized acoustic communication module, a diver can direct the fish by sending commands such as speed, turning angle, and dynamic vertical diving. This work builds on previous generations of robotic fish that were restricted to one plane in shallow water and lacked remote control. Experimental results gathered from tests along coral reefs in the Pacific Ocean show that the robotic fish can successfully navigate around aquatic life at depths ranging from 0 to 18 meters. Furthermore, our robotic fish exhibits a lifelike undulating tail motion enabled by a soft robotic actuator design that can potentially facilitate a more natural integration into the ocean environment. We believe that our study advances beyond what is currently achievable using traditional thruster-based and tethered autonomous underwater vehicles, demonstrating methods that can be used in the future for studying the interactions of aquatic life and ocean dynamics.

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Section: Limitations and Future Stepsmentioning

confidence: 99%

Exploration of underwater life with an acoustically controlled soft robotic fish

et al. 2018

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“…Additionally, with smaller fixed size local maps, the computations are deterministic and could be achieved in real-time. Monocular vision-based reactive avoidance methods are proposed in [5], [18], [19] using visual perspective invariants. However, these approaches prioritise 'escaping' from the obstacles including marine life, while in this work we create a probabilistic elevation map of the terrain, which will enable the risk of collision to be managed.…”

Section: B Vision-based Underwater Terrain Mapping For Navigationmentioning

confidence: 99%

Close-Proximity Underwater Terrain Mapping Using Learning-based Coarse Range Estimation

Arain¹,

Dayoub²,

Rigby³

et al. 2020

Preprint

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This paper presents a novel approach to underwater terrain mapping for Autonomous Underwater Vehicles (AUVs) operating in close proximity to complex 3D environments. The proposed methodology creates a probabilistic elevation map of the terrain using a monocular image learningbased scene range estimator as a sensor. This scene range estimator can filter transient objects such as fish and lighting variations. The mapping approach considers uncertainty in both the estimated scene range and robot pose as the AUV moves through the environment. The resulting elevation map can be used for reactive path planning and obstacle avoidance to allow robotic systems to approach the underwater terrain as closely as possible. The performance of our approach is evaluated in a simulated underwater environment by comparing the reconstructed terrain to ground truth reference maps, as well as demonstrated using AUV field data collected within in a coral reef environment. The simulations and field results show that the proposed approach is feasible for obstacle detection and range estimation using a monocular camera in reef environments.

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An Attention Transfer Model for Human-Assisted Failure Avoidance in Robot Manipulations

Song

Peng

Luo

et al. 2021

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)

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Ethologically inspired reactive exploration of coral reefs with collision avoidance: Bridging the gap between human and robot spatial understanding of unstructured environments

Cited by 8 publications

References 21 publications

Exploration of underwater life with an acoustically controlled soft robotic fish

Exploration of underwater life with an acoustically controlled soft robotic fish

Close-Proximity Underwater Terrain Mapping Using Learning-based Coarse Range Estimation

An Attention Transfer Model for Human-Assisted Failure Avoidance in Robot Manipulations

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