An Optimal Motion Planning Method of 7-DOF Robotic Arm for Upper Limb Movement Assistance

Liu, Zemin; Ai, Qingsong; Liu, Yaojie; Zuo, Jie; Zhang, Xiong; Meng, Wei; Xie, Shane

doi:10.1109/aim.2019.8868594

Cited by 9 publications

(3 citation statements)

References 23 publications

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“…3 Taxonomy of the research methods for safe human-robot interaction of ARMs an unstructured workspace populated by different obstacles [53]. Liu et al proposed a method based on the Rapidly-Exploring Random Tree Star (RRT*) approach in combination with artificial potential fields (APF) to achieve a highaccuracy motion planning of an assistive arm [54].…”

Section: Assistive Robotic Manipulatorsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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Purpose of Review Research in assistive and rehabilitation robotics is a growing, promising, and challenging field emerged due to various social and medical needs such as aging populations, neuromuscular, and musculoskeletal disorders. Such robots can be used in various day-today scenarios or to support motor functionality, training, and rehabilitation. This paper reflects on the human-robot interaction perspective in rehabilitation and assistive robotics and reports on current issues and developments in the field. Recent Findings The survey on the literature reveals that new efforts are put on utilizing machine learning approaches alongside novel developments in sensing technology to adapt the systems with user routines in terms of activities for assistive systems and exercises for rehabilitation devices to fit each user's need and maximize their effectiveness. Summary A review of recent research and development efforts on human-robot interaction in assistive and rehabilitation robotics is presented in this paper. First, different subdomains in assistive and rehabilitation robotic research are identified, and accordingly, a survey on the background and trends of such developments is provided.

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Section: Assistive Robotic Manipulatorsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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“…When the amount of sampling points is sufficient, the RRT * algorithm will safely plan an optimal path, but the plan time will greatly increase. Liu [11] proposed the PGS_RRT * algorithm, which applies a new potential field force to the sampling phase and plans a feasible path. Garcí a [12] proposed the HD-RRT * algorithm, which minimizes a path-cost function designed to bias the tree growth in configuration space.…”

Section: Introductionmentioning

confidence: 99%

PRRT: An Intelligent Planning Algorithm with Memory

Chen

Kang

Zhao

et al. 2022

J. Phys.: Conf. Ser.

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This paper proposes a practically executable path planning method, namely, Pheromones-RRT(PRRT), for robots with a large joint range in a complex environment. To inter-activate with the real world, the point cloud is utilized as the scene information, while for sampling, the pheromones approach is designed to describe the pheromone content carried by each sampling point. During the sampling process, random sampling nodes are performed with a probability of ε, or those nodes with the highest pheromone content in the current sampling tree are selected with a probability of 1-ε and sampled in their neighborhood. To avoid the local minimum problem, the concept of pheromone volatile factor (PVF) is proposed, while in the expansion, double trees are also generated by PRRT in both cartesian and configuration spaces to improve the speed of the algorithm. The pheromone accumulation enables PRRT to certain learning abilities, reducing the randomness of the sampling process. Simulation results show that the proposed method can effectively plan an optimal obstacle avoidance path with satisfactory performances as compared with the RRT-Connect.

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“…848 Revista TECNIA Vol.31 N°2 Junio-Diciembre 2020 obstáculos fue desarrollado por Johan Borenstein et al [2] en el cual usa campos potenciales y fusión de sensores para que un robot móvil recorra un trayecto y no se detenga abruptamente ante un obstáculo. Zemin Liu et al [3] desarrolla una variación del algoritmo de árboles aleatorios estrella usando campos potenciales artificiales con el fin de reducir el tiempo de ejecución del algoritmo y obtener un tiempo de ejecución menor.…”

Section: Introduccionunclassified

Planificación de movimiento mediante algoritmo de campos potenciales con optimizacion de parametros aplicado a un manipulador antropomorfico de 6 GLD

Tacora

Zapata

Toribio

et al. 2021

TEC

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En este trabajo se desarrolla una variación del algoritmo de campos potenciales para la planificación de trayectorias que evita obstáculos aplicado a un manipulador antropomórfico de 6 grados de libertad. En primera instancia se generó el modelo de cinemática inversa basada en un proceso de control iterativo multivariable, luego se modificó el modelo agregando un vector de rotación obtenido por las fuerzas repulsivas entre el obstáculo y las seis articulaciones del robot de manera que el manipulador pueda encontrar una ruta que evite el obstáculo y alcance una posición objetivo. Este modelo final de cinemática inversa con campos potenciales genera trayectorias que dependen del parámetro de velocidad de optimización y de los coeficientes de campos vectoriales. Con el objetivo de optimizar las trayectorias se generó una base de datos con los puntos iniciales, finales y de obstáculos de diferentes trayectorias con sus respectivos parámetros optimizados para entrenar una red neuronal supervisada. Los resultados muestran que la red neuronal debe entrenarse con una mayor cantidad de datos debido a que se calculan parámetros erróneos para ciertas posiciones iniciales y finales. Finalmente, la simulación del manipulador de 6 grados de libertad que sigue la trayectoria generada por el modelo de cinemática inversa y campos potenciales con los parámetros optimizados calculados empíricamente resultan en un modelo con un comportamiento adecuado logrando evitar los obstáculos.

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An Optimal Motion Planning Method of 7-DOF Robotic Arm for Upper Limb Movement Assistance

Cited by 9 publications

References 23 publications

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Human-Robot Interaction in Rehabilitation and Assistance: a Review

PRRT: An Intelligent Planning Algorithm with Memory

Planificación de movimiento mediante algoritmo de campos potenciales con optimizacion de parametros aplicado a un manipulador antropomorfico de 6 GLD

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