Study on Obstacle Avoidance Strategy Using Multiple Ultrasonic Sensors for Spherical Underwater Robots

Li, Chunying; Guo, Shuxiang; Guo, Jian

doi:10.1109/jsen.2022.3220246

Cited by 16 publications

(4 citation statements)

References 38 publications

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“…Despite various developed CCPP algorithms, the special operation mode makes them not perfectly appropriate for AUH's navigation control strategy. The existence of an obstacle is perceived by the distance information given by a horizontally mounted single beam range sonar/echo sounder (as can be seen in Figure 2), and it obviously distinguishes from other robots, on which LiDAR [23], infrared distance sensor, ultrasonic sensor [24], millimeter wave radar [25], camera, and multi-beam sonar [26], etc. are frequently used.…”

Section: Introductionmentioning

confidence: 99%

A Complete Coverage Path Planning Approach for an Autonomous Underwater Helicopter in Unknown Environment Based on VFH+ Algorithm

Ma,

Zou,

2024

JMSE

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An Autonomous Underwater Helicopter (AUH) is a disk-shaped, multi-propelled Autonomous Underwater Vehicle (AUV), which is intended to work autonomously in underwater environments. The near-bottom area sweep in unknown environments is a typical application scenario, in which the complete coverage path planning (CCPP) is essential for AUH. A complete coverage path planning approach for AUH with a single beam echo sounder, including the initial path planning and online local collision avoidance strategy, is proposed. First, the initial path is planned using boustrophedon motion. Based on its mobility, a multi-dimensional obstacle sensing method is designed with a single beam range sonar mounted on the AUH. The VFH+ algorithm is configured for the heading decision-making procedure before encountering obstacles, based on their range information at a fixed position. The online local obstacle avoidance procedure is simulated and analyzed with variations of the desired heading direction and corresponding polar histograms. Finally, several simulation cases are set up, simulated and compared by analyzing the heading decision in front of different obstacle situations. The simulation results demonstrate the feasibility of the complete coverage path planning approach proposed, which proves that AUH completing a full coverage area sweep in unknown environments with a single beam sonar is viable.

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Section: Introductionmentioning

confidence: 99%

A Complete Coverage Path Planning Approach for an Autonomous Underwater Helicopter in Unknown Environment Based on VFH+ Algorithm

Ma,

Zou,

2024

JMSE

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“…Various sensor-based approaches are employed in underwater robotics for obstacle detection and navigation in their immediate environment. Commonly used techniques for obstacle avoidance include sonar [3,4], cameras [5,6], or LiDAR [7][8][9]. Current underwater imaging sonar technologies such as the Farsounder-1000 (Farsounder, Warwick, RI, USA), EchoPilot FLS 3D (Daniamant, Slangerup, Denmark), and Echoscope4G (Coda Octopus, Edinburgh, UK) are used for obstacle avoidance.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Submerged MEMS Ultrasonic Sensors for Underwater Obstacle Avoidance Application

Wang,

Zhang,

Wang

et al. 2024

Remote Sensing

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Ultrasound is a powerful and versatile technology that has been applied extensively in medicine and scientific research. The development of miniature underwater robots focuses on achieving specific tasks, such as surveys and inspections in confined spaces. However, traditional sonar has limited use in micro underwater robots due to its large size and heavy power demands. Conversely, capacitive micromechanical ultrasonic transducers (CMUTs) offer various advantages, including a wide bandwidth, compact size, and integration feasibility. These attributes make CMUTs a candidate for obstacle avoidance in micro underwater robots. Hence, a novel CMUT structure using Si-Si bonding is proposed. In this design, a membrane isolation layer replaces the cavity bottom isolation layer, simplifying the process and improving bond reliability. A finite element model of the CMUT was constructed in COMSOL and numerically assessed for the CMUT’s operating frequency, collapse voltage, and submerged depth. The CMUT, manufactured using micro-electro-mechanical system (MEMS) technology, undergoes waterproofing with PDMS—A material with similar acoustic impedance to water and corrosion resistance. Underwater tests reveal the CMUT’s resonant frequency in water as approximately 2 MHz, with a −3 dB bandwidth of 108.7%, a transmit/receive beam width of 7.3°, and a standard deviation of measured distance from the true distance of less than 0.05. These outcomes suggest that CMUTs hold promise in obstacle avoidance applications for fish-shaped underwater robots.

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“…The two classic algorithms mentioned above can basically realize the local planning for most robots in most static environments, but these algorithms do not take the movement information of obstacles into consideration, and they all regard obstacles as static obstacles, which causes the planned trajectory to be only currently optimal, regardless of the future positions of the obstacles, so the obstacle avoidance effect in a dynamic environment is not good enough. However, robot obstacle avoidance is systematic work that not only needs path planners [18,19] but also needs to combine obstacle perception [20,21], robot control [22], trajectory tracking [23,24], and localization [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Local Path Planner for Mobile Robot Considering Future Positions of Obstacles

Ou,

You,

2024

Processes

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Local path planning is a necessary ability for mobile robot navigation, but existing planners are not sufficiently effective at dynamic obstacle avoidance. In this article, an improved timed elastic band (TEB) planner based on the requirements of mobile robot navigation in dynamic environments is proposed. The dynamic obstacle velocities and TEB poses are fully integrated through two-dimensional (2D) lidar and multi-obstacle tracking. First, background point filtering and clustering are performed on the lidar points to obtain obstacle clusters. Then, we calculate the data association matrix of the obstacle clusters of the current and previous frame so that the clusters can be matched. Thirdly, a Kalman filter is adopted to track clusters and obtain the optimal estimates of their velocities. Finally, the TEB poses and obstacle velocities are associated: we predict the obstacle position corresponding to the TEB pose through the detected obstacle velocity and add this constraint to the corresponding TEB pose vertex. Then, a pose sequence considering the future positions of obstacles is obtained through a graph optimization algorithm. Compared with the original TEB, our method reduces the total running time by 22.87%, reduces the running distance by 19.23%, and increases the success rate by 21.05%. Simulations and experiments indicate that the improved TEB enables robots to efficiently avoid dynamic obstacles and reach the goal as quickly as possible.

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Study on Obstacle Avoidance Strategy Using Multiple Ultrasonic Sensors for Spherical Underwater Robots

Cited by 16 publications

References 38 publications

A Complete Coverage Path Planning Approach for an Autonomous Underwater Helicopter in Unknown Environment Based on VFH+ Algorithm

A Complete Coverage Path Planning Approach for an Autonomous Underwater Helicopter in Unknown Environment Based on VFH+ Algorithm

Investigation of Submerged MEMS Ultrasonic Sensors for Underwater Obstacle Avoidance Application

Local Path Planner for Mobile Robot Considering Future Positions of Obstacles

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