Optimal trajectory planning of robot manipulators in the presence of moving obstacles

Saramago, Sezimária de Fátima Pereira; Steffen, Valder

doi:10.1016/s0094-114x(99)00062-2

Cited by 92 publications

(43 citation statements)

References 7 publications

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“…Simulated results were reported for the above methods considering two-link planar manipulator. A method to generate optimal trajectory considering moving obstacles in workspace was presented [10]. Two-link planar manipulator was considered for simulation purpose by considering the optimal traveling time and minimum mechanical energy of the actuators.…”

Section: Past Workmentioning

confidence: 99%

Spline Based Trajectory Planning for Cooperative Crane Lifts

Bhaskar¹,

Babu²,

Varghese³

2006

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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This paper reports the work done towards planning the trajectory for cooperative crane lifts. The location of the hook points between the pick and place positions are determined using a path-planner. These are inputs to the trajectory planner. The goal of the trajectory planner is to connect all the path-points while ensuring the overshoots, velocities, accelerations and jerk for each degree of freedom to be within acceptable limits for the system. A number of alternate techniques are available for defining the trajectory between the path-points. This paper reports on the evaluation of algebraic and trigonometric splines for trajectory planning. Splines of various orders were initially evaluated for a single joint. This evaluation found that 4 th order trigonometric splines were most appropriate. Hence, this was applied to a lift problem involving the 2x4 DOF cooperative manipulator system and the results are presented.

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Section: Past Workmentioning

confidence: 99%

Spline Based Trajectory Planning for Cooperative Crane Lifts

Bhaskar¹,

Babu²,

Varghese³

2006

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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“…(18), constitute a boundary value problem, or a twopoint-boundary-value (TPBV) problem, of second order that is suitable for handling by the ®nite element method with any C 0 (or higher) class elements [9]. However, for mechanical systems, matrix D is singular because all terms in the top row of matrix B de®ned by Eq.…”

Section: Optimal Controlmentioning

confidence: 99%

“…A thorough review of other analytical and numerical methods for solving directly the equations resulting from the Pontryagin principle and governing the optimal maneuvers can be found in [7]. Theoretically, optimal control problems can also be solved by the parametric optimisation methods [8,9]. Because of a large number of parameters that must be used to represent the trajectory and controls, these methods require a substantial computational effort and provide less accurate results.…”

Section: Introductionmentioning

confidence: 99%

Beam analogy for optimal control of linear dynamic systems

Szyszkowski

Grewal

2000

Computational Mechanics

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Optimal control problems for linear dynamic systems with quadratic performance index are solved using the beam analogy. The governing equations for the optimal maneuver are derived in the form of coupled fourth order differential equations in the time domain. These equations are uncoupled using modal variables. Next, each independent equation is made analogous to the corresponding problem of a beam on an elastic foundation. The beam problem in the spatial domain is solved using standard FEM software. Finally the FEM results are transferred back to the time domain where they represent the optimal trajectories and controls for the dynamic system.

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“…Examples of energy optimal trajectory planning are provided in some literatures. Both optimal travelling time and minimum mechanical energy of the actuators are considered together as objective functions in some literatures [5,6] .…”

Section: Introductionmentioning

confidence: 99%

“…When moving obstacles share the same workspace occupied by the robot manipulator, the optimisation of the trajectory defined by the end-effector is complex [1,5,6] . This complexity is associated with the large number of constraints to be taken into account by the optimiser.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary trajectory planning for an industrial robot

Saravanan¹,

Ramabalan²,

Balamurugan³

et al. 2010

Int. J. Autom. Comput.

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This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (AdeptOne XL robot) in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE), have been used for the optimization. Two methods (normalized weighting objective functions and average fitness factor) are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.

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Optimal trajectory planning of robot manipulators in the presence of moving obstacles

Cited by 92 publications

References 7 publications

Spline Based Trajectory Planning for Cooperative Crane Lifts

Spline Based Trajectory Planning for Cooperative Crane Lifts

Beam analogy for optimal control of linear dynamic systems

Evolutionary trajectory planning for an industrial robot

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