Minimum-time control of robotic manipulators with geometric path constraints

Shin, Kang G.; McKay, Neil David

doi:10.1109/tac.1985.1104009

Cited by 851 publications

(21 citation statements)

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“…The problem of generating time-optimal, dynamicallyfeasible trajectory of a given path without considering contact was initially solved by Bobrow et al [4] and Shin and McKay [26] and later enhanced by [7,8,18,27]. Recent work has extended the time-scaling problem to handle frictional contact [15].…”

Section: Related Workmentioning

confidence: 99%

Robust Trajectory Optimization Under Frictional Contact with Iterative Learning

Luo

Hauser²

2015

Robotics: Science and Systems XI

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Abstract-Optimization is often difficult to apply to robots due to the presence of modeling errors, which may cause constraints to be violated during execution on a real robot. This work presents a method to optimize trajectories with large modeling errors using a combination of robust optimization and parameter learning. In particular it considers the problem of computing a dynamically-feasible trajectory along a fixed path under frictional contact, where friction is uncertain and actuator effort is noisy. It introduces a robust time-scaling method that is able to accept confidence intervals on uncertain parameters, and uses a convex parameterization that allows dynamically-feasible motions under contact to be computed in seconds. This is combined with an iterative learning method that uses feedback from execution to learn confidence bounds on modeling parameters. Experiments on a manipulator performing a "waiter" task, on which an object is moved on a carried tray as quickly as possible, demonstrate this method can compensate for modeling uncertainties within a handful of iterations.

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Section: Related Workmentioning

confidence: 99%

Robust Trajectory Optimization Under Frictional Contact with Iterative Learning

Luo

Hauser²

2015

Robotics: Science and Systems XI

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“…Introduction W ITH rising fuel costs it is desirable to improve the fuel efficiency of current aircraft operations subject to aircraft performance and scheduling constraints. Such a problem can be naturally cast as an optimal motion planning problem, which is a common problem encountered in many industrial and transportation systems, including robotic arms [1][2][3][4], ground vehicles [5][6][7][8], and aircraft [9,10]. Although optimal motion planning problems can be solved directly using numerical optimization techniques [11][12][13][14][15][16][17] the number of the required computations may grow to impractical levels, especially for real-time applications.…”

Section: Nomenclaturementioning

confidence: 99%

Analysis of Energy-Optimal Aircraft Landing Operation Trajectories

Zhao

Tsiotras

2013

Journal of Guidance, Control, and Dynamics

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This paper presents a method for the energy-optimal operation of a fixed-wing aircraft tracking a prescribed landing path in the three-dimensional space with a fixed time of arrival. The problem is converted to an optimal control problem with one state variable, which is subject to state and control input constraints along the path. It is shown that the solution to this energy-optimal tracking problem provides a good approximation to the minimum-fuel problem. The switching structure of the optimal solution is analyzed, and a semi-analytical method is proposed for computing the optimal solution. Compared to standard numerical optimization methods the proposed method is guaranteed to converge to the optimal solution, and it is computationally much more efficient. Numerical examples are presented to demonstrate the validity of the proposed approach. As verified by these numerical results the proposed energy-optimal solution can help improve aircraft fuel efficiency during the landing phase.

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“…Since the desired path of the robot is already defined, a scalar path coordinate (θ(t)) can be used to represent robot position on the path [4][5][6][7]. The major advantage of the scalar path coordinate is that the high dimensional state-space model of the robotic system can be reduced.…”

Section: Introductionmentioning

confidence: 99%

Path Tracking Algorithms for Non-Convex Waiter Motion Problem

Nagy

Csorvási

Vajk

2018

Period. Polytech. Elec. Eng. Comp. Sci.

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Originally, motion planning was concerned with problems such as how to move an object from a start to a goal position without hitting anything. Later, it has extended with complications such as kinematics, dynamics, uncertainties, and also with some optimality purpose such as minimum-time, minimum-energy planning. The paper presents a time-optimal approach for robotic manipulators.A special area of motion planning is the waiter motion problem, in which a tablet is moved from one place to another as fastas possible, avoiding the slip of the object that is placed upon it. The presented method uses the direct transcription approach for the waiter problem, which means a optimization problem is formed in order to obtain a time-optimal control for the robot. Problem formulation is extended with a non-convex jerk constraints to avoid unwanted oscillations during the motion. The possible local and global solver approaches for the presented formulation are discussed, and the waiter motion problem is validated by real-life experimental results with a 6-DoF robotic arm.Keywords motion planning, minimum-time control, time-optimal control, convex optimisation, robot control 1 Introduction Time-optimal motion planning has been a topic of active research since the 1980. Minimum-time algorithms can maximize productivity, and reduce energy consumption of the robotic system. Direct approaches [1] or one step methods solve the entire problem in one step. In general it is a highly difficult task, since both the geometric constraints (including collision avoidance), and the timing along this geometric path (including dynamic limitation) have to be optimized.As an alternative to direct approach, the motion planning problem is often decoupled [2,3]. First, a high-level geometry path planner determines a path for the robot considering geometric constraints and ignoring system dynamics. In the next stage (path tracking), a velocity profile for a predefined path is generated, where all constraints of the robot are applied for the fixed path. Decoupled approach is preferred to direct approach for its lower computational time.In this paper, we will focus on the second stage of the decoupled motion planning approach. Since the desired path of the robot is already defined, a scalar path coordinate

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Minimum-time control of robotic manipulators with geometric path constraints

Cited by 851 publications

References 5 publications

Robust Trajectory Optimization Under Frictional Contact with Iterative Learning

Robust Trajectory Optimization Under Frictional Contact with Iterative Learning

Analysis of Energy-Optimal Aircraft Landing Operation Trajectories

Path Tracking Algorithms for Non-Convex Waiter Motion Problem

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