Time-Optimal Path Parameterization of Rigid-Body Motions: Applications to Spacecraft Reorientation

Nguyễn, Huy Hoàng; Pham, Quang-Cuong

doi:10.2514/1.g001600

Cited by 16 publications

(9 citation statements)

References 12 publications

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“…Methods in this paper are applicable to a broad class of agents with second order dynamics [14], including models of space vehicles, cars [15], [18], and Dubins' planes [19]. As a running example, we consider a fully actuated multicopter, whose dynamics are given by [20]…”

Section: B Problem Descriptionmentioning

confidence: 99%

Joint Feature Selection and Time Optimal Path Parametrization for High Speed Vision-Aided Navigation

Spasojevic

Murali

Karaman

2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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We study a problem in vision-aided navigation in which an autonomous agent has to traverse a specified path in minimal time while ensuring extraction of a steady stream of visual percepts with low latency. Vision-aided robots extract motion estimates from the sequence of images of their on-board cameras by registering the change in bearing to landmarks in their environment. The computational burden of the latter procedure grows with the range of apparent motion undertaken by the projections of the landmarks, incurring a lag in pose estimates that should be minimized while navigating at high speeds. This paper addresses the problem of selecting a desired number of landmarks in the environment, together with the time parametrization of the path, to allow the agent execute it in minimal time while both (i) ensuring the computational burden of extracting motion estimates stays below a set threshold and (ii) respecting the actuation constraints of the agent. We provide two efficient approximation algorithms for addressing the aforementioned problem. Also, we show how it can be reduced to a mixed integer linear program for which there exist well-developed optimization packages. Ultimately, we illustrate the performance of our algorithms in experiments using a quadrotor.

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Section: B Problem Descriptionmentioning

confidence: 99%

Joint Feature Selection and Time Optimal Path Parametrization for High Speed Vision-Aided Navigation

Spasojevic

Murali

Karaman

2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…The trajectory generation process is subject to the dynamics constraints of the underlying system. Finding time-optimal trajectories for robots with many degrees of freedom (DOFs) subject to complex dynamics and geometric constraints is a challenging problem that arises naturally in many robotics applications ranging from welding and painting to humanoid robots [1] and even spacecraft [2]. In practice, conservative safety constraints (e.g., by assuming quasistatic dynamics) are often used to simplify the trajectory generation problem, but this leads to either sub-optimal performance or more powerful hardware requirements than strictly necessary.…”

Section: Introductionmentioning

confidence: 99%

A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints

Butler

Moll

Kavraki

2020

Springer Proceedings in Advanced Robotics

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This paper presents a new algorithm which generates time-optimal trajectories given a path as input. The algorithm improves on previous approaches by generically handling a broader class of constraints on the dynamics. It eliminates the need for heuristics to select trajectory segments that are part of the optimal trajectory through an exhaustive, but efficient search. We also present an algorithm for computing all achievable velocities at the end of a path given an initial range of velocities. This algorithm effectively computes bundles of feasible trajectories for a given path and is a first step toward a new generation of more efficient kinodynamic motion planning algorithms. We present results for both algorithms using a simulated WAM arm with a Barrett hand subject to dynamics constraints on joint torque, joint velocity, momentum, and end effector velocity. The new algorithms are compared with a state-of-the-art alternative approach.

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“…Accordingly, it is proven that a bang-bang solution, in terms of the acceleration of the tip along the path, s, accounts for the problem. This means that the solution curve in the s − ṡ plane could be obtained by successively integrating the maximum and minimum values of s. 1 This method, mainly known as the numerical integration method, 2 has been widely used in previous studies for time-optimal solutions in both normally actuated 1,[3][4][5][6][7][8] and over-actuated [9][10][11][12][13][14][15][16][17] robots. Guaranteed convergence of solution, low computational cost, and providing the solution directly in the trajectory space are of main advantages to this approach.…”

Section: Introductionmentioning

confidence: 99%

A computationally efficient algorithm to find time-optimal trajectory of redundantly actuated robots moving on a specified path

Mansouri

Sadigh²,

Fazeli³

2018

Robotica

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A time-optimal problem for redundantly actuated robots moving on a specified path is a challenging problem. Although the problem is well explored and there are proposed solutions based on phase plane analysis, there are still several unresolved issues regarding calculation of solution curves. In this paper, we explore the characteristics of the maximum velocity curve (MVC) and propose an efficient algorithm to establish the solution curve. Then we propose a straightforward method to calculate the maximum or minimum possible acceleration on the path based on the pattern of saturated actuators, which substantially reduces the computational cost. Two numerical examples are provided to illustrate the issues and the solutions.

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Time-Optimal Path Parameterization of Rigid-Body Motions: Applications to Spacecraft Reorientation

Cited by 16 publications

References 12 publications

Joint Feature Selection and Time Optimal Path Parametrization for High Speed Vision-Aided Navigation

Joint Feature Selection and Time Optimal Path Parametrization for High Speed Vision-Aided Navigation

A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints

A computationally efficient algorithm to find time-optimal trajectory of redundantly actuated robots moving on a specified path

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