Obstacle Avoidance Using Multiobjective Optimization and a Dynamic Obstacle Manager

Benjamin, Michael R.; DeFilippo, Michael; Robinette, Paul; Novitzky, Michael

doi:10.1109/joe.2019.2896504

Cited by 28 publications

(8 citation statements)

References 82 publications

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“…For example, MOOS-IvP is a MOOS application designed to provide autonomy on robotic platforms and is particularly well-suited to marine vehicles. In Figure 10, IvP behaviours are depicted as they determine how the vehicle responds to its environment in pursuit of a defined goal [44].…”

Section: Figure 9 a Moos Communitymentioning

confidence: 99%

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Integration of Stereo Vision and MOOS-IvP for Enhanced Obstacle Detection and Navigation in Unmanned Surface Vehicles

Alhattab,

Abidin,

Faizabadi

et al. 2023

IEEE Access

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This paper addresses the development of a stereo vision-based obstacle avoidance system using MOOS-IvP for small and medium-sized Unmanned Surface Vehicles (USVs). Existing methods predominantly rely on optical sensors such as LiDAR and cameras to discern maritime obstacles within the short-to mid-range distances. Nonetheless, conventional cameras encounter challenges in water conditions that curtail their effectiveness in localizing obstacles and planning paths. Furthermore, LiDAR has limitations regarding angular resolution and identifying objectness due to data sparsity. To overcome these limitations, our proposed system leverages a stereo camera equipped with enhanced angular resolution to augment situational awareness. The system employs recursive estimation techniques to ascertain the position and dimensions of proximate obstacles, transmitting this information to the onboard control unit, where MOOS-IvP behaviour-based software produces navigation decisions. Through the real-time fusion of data obtained from the stereo vision system and navigational data, the system is able to achieve Enhance Situational Awareness (ESA) and facilitate well-informed navigation decisions. Developing a state-of-theart maritime object detection technique, the system adeptly identifies obstacles and swiftly responds via a vision integration protocol. During field tests, our system proves the efficacy of the proposed ESA approach. This paper also presents a comprehensive analysis and discussion of the results derived from deploying the proposed system on the Suraya Surveyor USV platform across numerous scenarios featuring diverse obstacles. The results from these various scenarios demonstrate the system's accurate obstacle detection capabilities under challenging conditions and highlight its significant potential for safe USV operations.

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Section: Figure 9 a Moos Communitymentioning

confidence: 99%

“…The mode structure is comprised of M unique mission modes and the set of behaviors with B unique behaviors. Each mode is defined by a unique name and set of logic conditions, whereas each behavior is defined by a unique name and set of configuration parameters for obstacle avoidance [44].…”

Section: Figure 9 a Moos Communitymentioning

confidence: 99%

Integration of Stereo Vision and MOOS-IvP for Enhanced Obstacle Detection and Navigation in Unmanned Surface Vehicles

Alhattab,

Abidin,

Faizabadi

et al. 2023

IEEE Access

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show abstract

“…Inverse kinematics of the manipulator is to solve the corresponding joint variables through the pose of the end of the manipulator [7]. But the inverse kinematics equation is really a nonlinear problem, in the process of solving, it needs to couple multiple angles, especially the five axis redundant manipulator studied in this paper, there are infinitely many inverse solutions, so we need to choose a group of inverse solutions according to the actual situation.…”

Section: Inverse Kinematics Analysis Of Manipulatormentioning

confidence: 99%

Dynamic obstacle avoidance and trajectory planning of five-axis redundant industrial manipulator

Ma¹

2023

J. vibroeng.

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Aiming at the problem that five axis redundant industrial manipulator dynamic obstacle avoidance and trajectory planning algorithm does not consider the minimum difference of each joint of the manipulator, which leads to low success rate of obstacle avoidance planning, slow convergence speed of path cost and long time of obstacle avoidance planning, a simulation study on dynamic obstacle avoidance trajectory planning of five axis redundant industrial manipulator is proposed. According to the D-H rule, the coordinate system of each link joint of the five axis redundant industrial manipulator is established, and the forward and inverse kinematics of the five axis redundant industrial manipulator is analyzed. AABB's hierarchical bounding box tree algorithm is used to detect the collision of five axis redundant industrial manipulator. This paper uses harmony search algorithm to plan the obstacle avoidance path of five axis redundant industrial manipulator, determines the objective function and constraints of the optimization problem, sets algorithm parameters, initializes harmony memory, creates new harmony, updates harmony memory, checks and searches the target state, achieves the maximum number of iterations, and realizes the dynamic obstacle avoidance and trajectory planning of five axis redundant industrial manipulator. The experimental results show that the path cost of the proposed algorithm converges faster, and can effectively improve the success rate of obstacle avoidance planning and shorten the time of obstacle avoidance planning.

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“…Huang X et al used binocular vision techniques in mobile robots to perform behavioral perception of moving objects in the environment and dynamic processing based on behavioral information of objects that can move in the outside world [12]. Benjamin M R et al worked out a stereo vision system using dual camera baseline elongation to achieve accurate self-localization and path navigation of the detector [13]. The system logarithmically optimizes and probabilistically estimates the captured images at different locations to obtain high accuracy parallax and calculates the individual 3D spatial coordinates of the objects in the recognized images, allowing the detector to perform real-time 3D reconstruction of the surrounding environment.…”

Section: Related Workmentioning

confidence: 99%

Optimization of Dynamic Obstacle Avoidance Path of Multirotor UAV Based on Ant Colony Algorithm

Yang

Chen

2022

Wireless Communications and Mobile Computing

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In this paper, the real-time path avoidance problem of multirotor UAV in the case of sudden obstacles in two-dimensional environment is studied. The principle, model, and application of ant colony algorithm are analyzed. On this basis, the adaptive dynamic window ant colony algorithm is proposed, and the adaptive dynamic window method is designed; the heuristic function of adding obstacle detection factors and the double pheromone update strategy are made to the ant colony algorithm, and the improved ant colony algorithm is used to replan the path within the dynamic window that can be automatically adjusted to achieve the purpose of obstacle avoidance. A real-time simulation experiment of path planning was conducted by constructing an environment map in MATLAB. The simulation results show that with the continuous increase of the number of sudden obstacles, the real-time replacement path of multirotor UAV also gradually increases, and when approaching the obstacles, the replacement path is more dense, indicating that the adaptive window ant colony algorithm can be applied to dynamic path replacement, and the multirotor UAV can realize dynamic obstacle avoidance path optimization under the condition of sudden obstacles in a short time.

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Obstacle Avoidance Using Multiobjective Optimization and a Dynamic Obstacle Manager

Cited by 28 publications

References 82 publications

Integration of Stereo Vision and MOOS-IvP for Enhanced Obstacle Detection and Navigation in Unmanned Surface Vehicles

Integration of Stereo Vision and MOOS-IvP for Enhanced Obstacle Detection and Navigation in Unmanned Surface Vehicles

Dynamic obstacle avoidance and trajectory planning of five-axis redundant industrial manipulator

Optimization of Dynamic Obstacle Avoidance Path of Multirotor UAV Based on Ant Colony Algorithm

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