A trajectory planning of redundant manipulators based on bilevel optimization

This work considers the optimization of fast path planning for spacecraft formation reconfiguration on libration point orbits. An adaptive surrogate model is proposed for solving the above optimization problem in abnormal conditions and/or emergency cases. First, a multi-layer optimization problem is established. In the outer loop of the multi-layer optimization, the nonlinear optimal control problem, taken as a dynamic optimization, is solved to obtain the optimal transfer paths of all spacecraft in the formation. In the inner loop of the multi-layer optimization, the parameter optimization problem, taken as a static optimization, is solved to obtain the states of all the spacecraft within the maximized area of the spacecraft formation. Then, an adaptive surrogate model is proposed. Because the multi-layer optimization problem is typically time-consuming and computationally expensive, the adaptive surrogate model is constructed using data drawn from the multi-layer optimization model and provides a fast approximation of the objective at new design points. Therefore, the adaptive surrogate model is feasible and cheap for spacecraft formation reconfiguration. Finally, numerical simulations show that the adaptive surrogate-based parameter optimization has advantages over the direct global optimization method. The accuracy, efficiency and robustness of the proposed adaptive surrogate model have also been compared between the different types of surrogate models.

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“…The radial basis function (RBF) method uses a linear combination of the basis functions to express the objective function as follows [23]:…”

Section: The Radial Basis Function Methodsmentioning

confidence: 99%

Adaptive surrogate model-based fast path planning for spacecraft formation reconfiguration on libration point orbits

Peng

Wang

2016

Aerospace Science and Technology

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“…The conventional path planning has been classified into two types, which are online path planning and offline path planning. The offline path planning will create the entire map for the surrounding area before starting the movement, and this approach uses all the information about the environment space that is required to compute the optimal solution …”

Section: Introductionmentioning

confidence: 99%

Establishing an emergency communication network and optimal path using multiple autonomous rover robots

Sakthitharan¹,

Jayashri²

2018

Concurrency and Computation

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Summary The natural calamity or disaster may destroy all communication networks especially a cellular network that relies on a tower. Although many solutions to an ad hoc wireless network have been proposed, forming a network covering a respective region with mobile robots toward optimal coverage remains to be an open problem. In this paper, we take the initiative to handle the optimal network coverage and path selection in disaster region with the help of multiple movable/rover robots. This paper consists of load balance distribution algorithm and optimal coverage algorithm applied to find the next optimally possible node location for all robots. Next, the robots maneuvering in an unknown disaster environment to identify the optimal path between the source and destination by using a particle swarm optimization algorithm. Finally, simulated results show that the algorithms can significantly improve the network coverage in the entire region, and the optimal path can effectively identify the optimal solution for all rover robots.

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“…Collision detection in task space depends mainly on two sub-problems: obstacle representation and collision detection of all components of the robot. For the sake of simplicity, many of the obstacle representation methods in task space use spherical representations [18]. When using a spherical representation, an obstacle is enclosed by the smallest sphere regardless of its shape; as a result, the representations of obstacles are larger than the real obstacles and the volume of obstacle-free spaces in the environment is smaller than the real obstacle-free spaces.…”

Section: Path Generation In Environments With Obstaclesmentioning

confidence: 99%

A task-driven algorithm for configuration synthesis of modular robots

İçer

Giusti

Althoff

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-This paper presents a time-efficient, task-based configuration synthesis algorithm for modular robot manipulators. One of the main challenges in modular manipulators is to find possible combinations of modules that are able to complete given tasks while avoiding obstacles in the environment. Most studies on modular robots focus on obtaining combinations of modules to achieve a given task without considering the required path planning in an environment with obstacles. In contrast to previous works, we present a configuration synthesis method for modular manipulators, considering collision detection and path planning in task space. Our simulations show that our approach finds possible combinations with reduced computational time compared to previous techniques.

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A trajectory planning of redundant manipulators based on bilevel optimization

Cited by 46 publications

References 27 publications

Adaptive surrogate model-based fast path planning for spacecraft formation reconfiguration on libration point orbits

Adaptive surrogate model-based fast path planning for spacecraft formation reconfiguration on libration point orbits

Establishing an emergency communication network and optimal path using multiple autonomous rover robots

A task-driven algorithm for configuration synthesis of modular robots

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