Comparison of Optimal Solutions to Real-Time Path Planning for a Mobile Vehicle

Yang, Jian; Qu, Zhihua; Wang, Jing; Conrad, Kevin L.

doi:10.1109/tsmca.2010.2044038

Cited by 41 publications

(18 citation statements)

References 15 publications

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“…Then it is straightforward to substitute the differential form of (4) into (31) and (32), which could directly yield (33) and (34). This completes the proof.…”

Section: A Kinodynamic Constraintsmentioning

confidence: 64%

“…Yet recalling the constraints g(c 6 respectively, which are identical to lines used in [34][35] and there may not be solutions for the two specific lines. This is why the parameterization method in (45) is used to find out more potentially feasible solutions from more directions in the parameter space.…”

Section: Suboptimal Solution To the Constrained Optimization Problmentioning

confidence: 99%

“…single optimal solutions of the proposed method are demonstrated. In [34], different optimal indexes for parametric method have been discussed and two relatively more effective solutions are proposed, which have been used to generate Path 2 and 5. Path 3 is based on basic geometric analytic solution of trajectory generation in [29], and Path 6 is for [35] that uses time-parametric trajectory models and optimal solution.…”

Section: A Optimal Trajectory Generation and Comparison Without Obstmentioning

confidence: 99%

“…It should be noted that in Fig.7 (f) the velocity and acceleration are both below their respective limitations as v max and a max , which means kinodynamic Energy optimal trajectories under different optimal solutions amidst mobile obstacles. Path 1, 2 and 3 are generated by the proposed suboptimal method (near minimum energy), energy optimal solutions in [34] and ordinary solutions in [29] respectively. Fig.…”

Section: ) Example 2 (Optimization In Dynamic Environments)mentioning

confidence: 99%

“…Length optimal trajectories under different optimal solutions amidst mobile obstacles. Path 4, 5 and 6 are generated by the proposed suboptimal method (near shortest path), length optimal solutions in [34] and [29] respectively. constraints are strictly obeyed.…”

Section: ) Example 2 (Optimization In Dynamic Environments)mentioning

confidence: 99%

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A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles

et al. 2015

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Abstract-In this paper, we present a suboptimal and analytical solution to the trajectory generation of mobile robots operating in a dynamic environment with moving obstacles. The proposed solution explicitly addresses both the robot kinodynamic constraints and the geometric constraints due to obstacles while ensuring the suboptimal performance to a combined performance metric. In particular, the proposed design is based on a family of parameterized trajectories, which provides a unified way to embed the kinodynamic constraints, geometric constraints, and performance index into a set of parameterized constraint equations. To that end, the suboptimal solution to the constrained optimization problem can be analytically obtained. The solvability conditions to the constraint equations are explicitly established, and the proposed solution enhances the methodologies of real-time path planning for mobile robots with kinodynamic constraints. Both the simulation and experiment results verify the effectiveness of the proposed method.

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“…Then it is straightforward to substitute the differential form of (4) into (31) and (32), which could directly yield (33) and (34). This completes the proof.…”

Section: A Kinodynamic Constraintsmentioning

confidence: 64%

Section: Suboptimal Solution To the Constrained Optimization Problmentioning

confidence: 99%

Section: A Optimal Trajectory Generation and Comparison Without Obstmentioning

confidence: 99%

Section: ) Example 2 (Optimization In Dynamic Environments)mentioning

confidence: 99%

Section: ) Example 2 (Optimization In Dynamic Environments)mentioning

confidence: 99%

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A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles

et al. 2015

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Optimal control applications and methods literature survey (no. 19-20)

2010

Optim. Control Appl. Meth.

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In order to keep readers up to date, the journal will contain a list of recently published journal articles relevant to the fields of optimal control, system optimization and applications six times a year. This list is compiled from a wide range of journals. Please note that even though the list has been broadly categorized these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Leonardo Giovanini at lgiovanini@fich.unl.edu.ar. OPTIMAL CONTROLChen L, Wu Z. Maximum principle for the stochastic optimal control problem with delay and application.

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