Time-Optimal Trajectory Generation for Path Following with Bounded Acceleration and Velocity

Kunz, T.; Stilman, Mike

doi:10.15607/rss.2012.viii.027

Cited by 77 publications

(90 citation statements)

References 5 publications

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“…Extensions to this address different path parametrizations [11], and dealing with velocity and torque limits [12] or dynamic singularities [13] . These papers do not address the completeness since combining a kinematic path planner with retiming for kinodynamic constraints are independent steps.…”

Section: Related Workmentioning

confidence: 99%

Motion planning for smooth pickup of moving objects

Menon

Cohen

Likhachev

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Kinematic planning for robotic arms has been shown to be capable of planning for robust manipulation of static objects. However, this approach falls short when manipulating moving objects such as picking up a jar off of a conveyor belt at a bottling plant. The challenge in carefully picking up moving objects is that these actions require motions that do not involve large decelerations, to avoid jerking the object, as well as figuring out the proper time in which the object can be picked up. We present a search-based kinodynamic motion planning algorithm that generates a timeparameterized trajectory for both the arm and end-effector, capable of carefully picking up the object at the earliest feasible point in its trajectory. To combat the high-dimensionality of the time-parameterized kinodynamic planning problem, our approach employs informative heuristics and adaptive dynamic motion primitives. To validate our approach, we used a 7DOF manipulator on Willow Garage's PR2 robot to pickup objects off of a conveyor belt. We also provide a detailed set of results that demonstrate the planner's ability to generate consistent, low cost trajectories for manipulation.

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Section: Related Workmentioning

confidence: 99%

Motion planning for smooth pickup of moving objects

Menon

Cohen

Likhachev

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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“…This approach may fail to achieve the same quality as full trajectory optimization because there is a risk of computing a path in stage 1 that will not yield a fast time parameterization in stage 2, but results are usually satisfactory in practice given their orders of magnitude speed up. The classical method integrates the time scaling variable along dynamic limits [2], but as identified in [9,13], this method was found to suffer from numerical instability issues at dynamic singularities. Recent work formulated a more robust convex optimization approach that casts time optimization as a second-order cone program (SOCP) [15].…”

Section: Related Workmentioning

confidence: 99%

“…For the 63 DOF humanoid described below, computation times are reduced by two orders of magnitude. [9] of the classical exact time-scaling algorithm [2] (code accessed May 2012). B-spline path derivative calculations were integrated into the code, and the method was run on the B-spline paths produced in Fig.…”

Section: B Time Scalingmentioning

confidence: 99%

Fast Interpolation and Time-Optimization on Implicit Contact Submanifolds

Hauser¹

2013

Robotics: Science and Systems IX

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Abstract-This paper presents a method for generating smooth, efficiently-executable trajectories for robots under contact constraints, such as those encountered in legged locomotion and object manipulation. It consists of two parts. The first is an efficient, robust method for constructing C1 interpolating paths between configuration/velocity states on implicit manifolds. The second is a robust time-scaling method that solves for a minimum-time parameterization using a novel convex programming formulation. Simulation experiments demonstrate that the method is fast, scalable to high-dimensional robots, and numerically stable on humanoid robot locomotion and object manipulation examples.

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“…The robotic technology is used in various industry sectors [1], [2], [6], [7]. The problems that arise are complexity of planning a robot motion and real-time computation of the speed and location for the robotic arm motion; these can be computationally intensive and time-consuming.…”

Section: Introductionmentioning

confidence: 99%

“…The approach is not applicable to automatically generated paths with potentially dense waypoints. In [2] was presented a method to generate the time optimal trajectory along a given path within given bounds on acceleration and speed. The method assumes that the acceleration and speed of individual coordinates are limited.…”

Section: Introductionmentioning

confidence: 99%

Mixed Profile Method of Speed and Location for Robotic Arms Motion used for Precise Positioning

Matica¹,

Győrödi²,

Silaghi³

et al. 2018

ijacsa

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Abstract-The paper describes a new real-time computation method named Mixt Profile of Speed (MPS), which is used to obtain the value of speed, at every sampling period of time, during the acceleration and deceleration stage, whereas the motion has three stages: 1) acceleration, 2) motion with imposed constant speed, and 3) deceleration. The method will determinate the location of a robotic arm for every sampling period of time. The originality of this new computation method refers to the deceleration stage; it determines an accurate positioning at the end of the motion in a well determinate interval of time. During the forced constant motion stage, the trajectory is imposed and it is linear or circular. The ADNIA algorithm (numerical differential analysis interpolation algorithm) can be implemented at this stage (during the motion with imposed constant speed of the robotic arm) in order to ensure the maximum precision of the computation for the waypoints Cartesian coordinates.

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Time-Optimal Trajectory Generation for Path Following with Bounded Acceleration and Velocity

Cited by 77 publications

References 5 publications

Motion planning for smooth pickup of moving objects

Motion planning for smooth pickup of moving objects

Fast Interpolation and Time-Optimization on Implicit Contact Submanifolds

Mixed Profile Method of Speed and Location for Robotic Arms Motion used for Precise Positioning

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