A Simulation Framework for the Integration of Artificial Olfaction into Multi-Sensor Mobile Robots

Ojeda, Pepe; Monroy, Javier; González-Jiménez, Javier

doi:10.3390/s21062041

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…Future work on tactile-based approaches is about improving accuracy, and the applications are autonomous transport and perception [ 14 , 81 , 82 , 83 ]. Olfaction-based navigation approaches are implemented for transport [ 15 , 84 , 86 , 87 ], gas dispersion [ 85 ], and gas source localization [ 88 ]. The limitations of olfactory navigation include obstacle avoidance techniques, active searching, several odor plumes, and precise localization.…”

Section: Discussionmentioning

confidence: 99%

“…Ojeda et al [ 85 ] introduced a framework for integrating gas dispersal and sensing and computer vision, which modeled the visual representation of a gas plume. It defined the environment, simulated wind and gas dispersion data, and then integrated the results in Unity for plume rendering, sensor simulation, and environment visuals.…”

Section: Olfactory Navigationmentioning

confidence: 99%

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Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

2023

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Biological principles draw attention to service robotics because of similar concepts when robots operate various tasks. Bioinspired perception is significant for robotic perception, which is inspired by animals’ awareness of the environment. This paper reviews the bioinspired perception and navigation of service robots in indoor environments, which are popular applications of civilian robotics. The navigation approaches are classified by perception type, including vision-based, remote sensing, tactile sensor, olfactory, sound-based, inertial, and multimodal navigation. The trend of state-of-art techniques is moving towards multimodal navigation to combine several approaches. The challenges in indoor navigation focus on precise localization and dynamic and complex environments with moving objects and people.

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Section: Discussionmentioning

confidence: 99%

Section: Olfactory Navigationmentioning

confidence: 99%

Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

2023

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“…However, in daily life, for outdoor autonomous vehicle or indoor robots, if a single sensor is used for positioning and navigation, it is vulnerable to interference from external environmental factors and the sensor itself cannot meet the requirements of positioning accuracy and stability [7]. Therefore, the SLAM technology using multi-sensors information fusion, such as visual camera, laser radar and IMU, emerged.…”

Section: Introductionmentioning

confidence: 99%

Novel cartographer using an OAK-D smart camera for indoor robots location and navigation

Yong

Mokhtarzadeh

Xiao

2023

J. Phys.: Conf. Ser.

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In recent years, service robots have been widely used in people’s daily life, and with the development of more and more intelligence, people put forward higher requirements for autonomous positioning and navigation functions of robots. Like outdoor navigation, indoor navigation also needs the support of navigation data. Although the indoor positioning and navigation scheme based on cameras, lidars and other sensors is gradually developing, due to the complexity of the indoor structure, manual production of indoor navigation data is time-consuming and laborious, and the efficiency is relatively low. In order to solve the problem of low productivity and improve the accuracy of robot automatic navigation, we added a new type of intelligent camera, called OpenCV AI kit or OAK-D, and proposed a method to automatically build data files that can be used for indoor navigation and location services using indoor 3D point cloud data. This intelligent camera performs neural reasoning on chips that do not use GPUs. It can also use stereo drills for depth estimation, and use 4K color camera images as input to run the neural network model. Python API can be called to realize real-time detection of indoor doors, windows and other static objects. The target detection technology uses an artificial intelligence camera, and the robot can well identify and accurately mark on the indoor map. In this paper, a high-performance indoor robot navigation system is developed, and multisensor fusion technology is designed. Environmental information is collected through artificial intelligent camera (OAK-D), laser lidar, and data fusion is carried out. In the experiment part of this paper,The static fusion map module is created based on the laser sensor information and the sensor information of the depth camera, the hierarchical dynamic cost map module is created in the real-time navigation, and the global positioning of the robot is realized by combining the word bag model and the laser point cloud matching. Then a software system is realized by integrating each module. The experiment proves that the system is practical and effective, and has practical value.

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“…Considering the high cost of hardware platform and the high risk of physical tests, robot simulation technology has gradually become a feasible solution for algorithm verification [ 21 ]. For example, Ojeda et al [ 22 ] proposed a simulation framework based on GADEN and Unity Engine to integrate simulated olfaction and simulated vision into multi-sensor mobile robots. In [ 23 ], the authors developed a simulator to support the navigation activities of unmanned ground vehicles (UGV) based on ROS and Gazebo.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Modular UUV Simulation Platform

Zhang

et al. 2022

Sensors

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The complex and time-varying marine environment puts forward demanding requirements for the structural design and algorithm development of unmanned underwater vehicles (UUVs). It is inevitable to repeatedly evaluate the feasibility of autonomy schemes to enhance the intelligence and security of the UUV before putting it into use. Considering the high cost of the UUV hardware platform and the high risk of underwater experiments, this study aims to evaluate and optimize autonomy schemes in the manner of software-in-loop (SIL) simulation efficiently. Therefore, a self-feedback development framework is proposed and a multi-interface, programmable modular simulation platform for UUV based on a robotic operating system (ROS) is designed. The platform integrates the 3D marine environment, UUV models, sensor plugins, motion control plugins in a modular manner, and reserves programming interfaces for users to test various algorithms. Subsequently, we demonstrate the simulation details with cases, such as single UUV path planning, task scheduling, and multi-UUV formation control, and construct underwater experiments to confirm the feasibility of the simulation platform. Finally, the extensibility of the simulation platform and the related performance analysis are discussed.

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A Simulation Framework for the Integration of Artificial Olfaction into Multi-Sensor Mobile Robots

Cited by 10 publications

References 36 publications

Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

Novel cartographer using an OAK-D smart camera for indoor robots location and navigation

Design and Implementation of a Modular UUV Simulation Platform

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