Vision-based smooth obstacle avoidance motion trajectory generation for autonomous mobile robots using Bézier curves

Simba, Kenneth Renny; Uchiyama, Naoki; Aldibaja, Mohammad; Sano, Shigenori

doi:10.1177/0954406215616986

Cited by 15 publications

(7 citation statements)

References 26 publications

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“…In this work, it was decided to use approximations by Bézier curves as these generate smooth curves and are currently used in different applications [19,31,32]. However, there is a wide possibility of degrees to be used for generating Bézier curves; therefore, it requires an optimization strategy that simplifies the selection of the optimal degree, nopt, of the Bézier curve for each of the graphite nodules contours.…”

Section: Optimization Of the Bezier Curve Degree Using Gamentioning

confidence: 99%

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

et al. 2017

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Abstract:The aim of this article is to develop a methodology that is capable of generating micro-scale models of Ductile Cast Irons, which have the particular characteristic to preserve the smoothness of the graphite nodules contours that are lost by discretization errors when the contours are extracted using image processing. The proposed methodology uses image processing to extract the graphite nodule contours and a genetic algorithm-based optimization strategy to select the optimal degree of the Bézier curve that best approximate each graphite nodule contour. To validate the proposed methodology, a Finite Element Analysis (FEA) was carried out using models that were obtained through three methods: (a) using a fixed Bézier degree for all of the graphite nodule contours, (b) the present methodology, and (c) using a commercial software. The results were compared using the relative error of the equivalent stresses computed by the FEA, where the proposed methodology results were used as a reference. The present paper does not have the aim to define which models are the correct and which are not. However, in this paper, it has been shown that the errors generated in the discretization process should not be ignored when developing geometric models since they can produce relative errors of up to 35.9% when an estimation of the mechanical behavior is carried out.

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Section: Optimization Of the Bezier Curve Degree Using Gamentioning

confidence: 99%

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

et al. 2017

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“…A real-time smooth trajectory generation method based on A* algorithm was proposed. 11 A fisheye lens with wide angle was used to capture the image. Only corners of the obstacle were detected, and a simple configuration space was generated in order to reduce the computational time.…”

Section: Introductionmentioning

confidence: 99%

A real-time obstacle avoidance and path tracking strategy for a mobile robot using machine-learning and vision-based approach

Singh

Bera

Chatti³

2022

SIMULATION

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In this paper, an obstacle avoidance and target tracking method for both indoor and outdoor mobile robots in dynamic environment is presented, and it aims to enhance autonomous navigation capability of such robots. In the proposed method, image processing and machine-learning approaches are considered. Since obstacles have differences in color and texture and in order to identify non-navigable areas, a monocular onboard camera is used to capture the road lanes by dealing with an image processing technique. The position of the robot with respect to road lane center during navigation is calculated on the basis of a proposed fuzzy logic rules set. In order to provide fast and robust computation, the Haar cascade classifier-based machine-learning technique has been exploited to detect the different sizes and shapes of the obstacles faced by the robot during its movement from source to destination. The dynamic model of a four-wheel mobile robot is initially developed using bond graph theory and then, the proposed obstacle-avoidance strategy is applied. The effectiveness and performance of the proposed method are tested under various simulation and experimentation scenarios. The behavior of the mobile robot for detecting and avoiding static obstacle for single and double road lane change environment is analyzed and discussed.

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Section: Introductionmentioning

confidence: 99%

“…In general, polynomial interpolation 5 is mainly used for planning in the joint space, while basic curves, such as lines and arcs, 6 are used for planning in the cartesian space. Moreover, indexes such as motion stability, 7 obstacle avoidance 8 and so on, can be optimised on the basis of the trajectory planning method. Correspondingly, optimisation algorithm combining with the indexes mentioned above, is used for trajectory optimisation, such as particle swarm optimisation (PSO) 9 and GA, 10 which could improve the characteristics of the robot trajectory.…”

Section: Introductionmentioning

confidence: 99%

Trajectory optimisation with musculoskeletal integration features for fracture reduction orthopaedic robot

Cui

Jiang

et al. 2022

Robotics Computer Surgery

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Background: Human body is an integrated system of bones and muscles. To date, there are insufficient studies on the effect of muscles on the trajectory planning of orthopaedic robot. To this end, based on a Stewart-Gough platform (6-UPU) fracture reduction orthopaedic robot, a musculoskeletal trajectory optimisation method was constructed for the interference of soft tissue during the reduction process.Methods: Firstly, pose description of the fracture reduction orthopaedic robot was introduced, and its working space was analysed. Secondly, an improved Hill muscle theory was used to construct the musculoskeletal system, and finite element analysis (FEA) was carried out. Thirdly, particle swarm optimisation (PSO) with variable weights was imported, and fracture reduction trajectory planning was obtained by quintic polynomial in the workspace. Then mathematical model for trajectory optimisation was presented, and targets of musculoskeletal optimisation were extracted, which include muscle energy consumption, robot-assisted repositioning time and trajectory length. In this sense, musculoskeletal integration trajectory optimisation method was put forward. Finally, comparative optimisation simulation with skeleton only and bone and muscle together were tested, and safety experiment with musculoskeletal integration was conducted.Results: A cone shape workspace was got, whose range can be defined as 635.14 mm on the X axis, 720 mm on the Y axis, and 240 mm on the Z axis, respectively. Besides, different FEA displacements revealed the effect of bone and muscle on the movement of the robot. Moreover, the optimal results with and without muscle had showed different movement time: the former consumed about 27 s, but the latter spent about 25 s. Additionally, the speed and acceleration of the drive rods can be obtained from zero to zero during the reset. Conclusions:The results show that the optimised trajectory obtained with this method is safe and reliable. Furthermore, the presence of muscle has great influence on the trajectory of robot, which could prolong the reduction time so as to prevent the occurrence of uneven soft and hard traction rate problem. This paper could be helpful for the future trajectory planning study of fracture reduction orthopaedic robot.

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Vision-based smooth obstacle avoidance motion trajectory generation for autonomous mobile robots using Bézier curves

Cited by 15 publications

References 26 publications

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

A real-time obstacle avoidance and path tracking strategy for a mobile robot using machine-learning and vision-based approach

Trajectory optimisation with musculoskeletal integration features for fracture reduction orthopaedic robot

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