Unified environment-adaptive control of accompanying robots using artificial potential field

Nakazawa, Kazushi; Takahashi, Keita; Kaneko, Masahide

doi:10.1109/hri.2013.6483570

Cited by 8 publications

(4 citation statements)

References 1 publication

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“…The potential field method [36] is a real time robot motion controlling method, in which potential fields are generated according to the properties of places or objects that may influence the motion of robot. The goal or sub-goals that the robot should move towards are set with attractive potential field, and they will generate an attractive force to make the robot get close.…”

Section: B Control Methods Based On Integrated Potential Fieldmentioning

confidence: 99%

Research on Design and Motion Control of a Considerate Guide Mobile Robot for Visually Impaired People

Zhang,

Okutsu,

Ochiai

et al. 2023

IEEE Access

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Guide mobile robot have been researched and developed for decades. However, current robot cannot guide the user to the destination considerately, since the status of the user and the properties of the obstacles are not considered, especially for the guiding work of servicing visually impaired people. In this paper, a guide mobile robot with an easy-to-hold handle is designed, a generation method of spatial risk map is proposed to evaluate the influences of potential spaces of objects and a motion control method based on spatial risk map considering potential occupied spaces of objects is proposed. The users are successfully guided to the destination naturally without influencing other pedestrians by avoiding entering the potential spaces of objects automatically, and they can adjust their moving status in their own will since the considerate robot can adaptively adjust its guide status to adapt to the user. Through comparing guiding experiments of different tasks for 10 blindfolded users, the proposed guide mobile robot is proven considerate by guiding the users adaptively and make other pedestrians feel comfortable by avoiding entering the potential spaces of objects automatically.INDEX TERMS Intelligent robots, autonomous systems, robot control, assistive robots, autonomous robots.

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Section: B Control Methods Based On Integrated Potential Fieldmentioning

confidence: 99%

Research on Design and Motion Control of a Considerate Guide Mobile Robot for Visually Impaired People

Zhang,

Okutsu,

Ochiai

et al. 2023

IEEE Access

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“…In the domain of HRI, Wang et al [80] applied adaptive control to robot navigation, where a social proxemics potential field is constructed and used to design a robot motion controller that is able to adapt its desired trajectory smoothly and at the same time comply with the proxemics contraints. Nakazawa et al [56] proposed a potential field imposing a repulsive fin to allow adaptive control of an accompanying robot, where the robot is able to adapt its relative position to the accompanied human in the presence of obstacles. Vitiello et al [78] proposed a neuro-fuzzy-Bayesian approach for adaptive control of a robot's proxemics behavior, where recognized human activities and human personality acquired by questionnaires are input into an adaptive neuro-fuzzy inference engine system (ANFIS) to determine a robot's stopping distance.…”

Section: Related Workmentioning

confidence: 99%

Learning to Engage with Interactive Systems

Meng

Lin

Francey

et al. 2020

J. Hum.-Robot Interact.

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Physical agents that can autonomously generate engaging, lifelike behavior will lead to more responsive and user-friendly robots and other autonomous systems. Although many advances have been made for one-toone interactions in well-controlled settings, physical agents should be capable of interacting with humans in natural settings, including group interaction. To generate engaging behaviors, the autonomous system must first be able to estimate its human partners' engagement level. In this article, we propose an approach for estimating engagement during group interaction by simultaneously taking into account active and passive interaction, and use the measure as the reward signal within a reinforcement learning framework to learn engaging interactive behaviors. The proposed approach is implemented in an interactive sculptural system in a museum setting. We compare the learning system to a baseline using pre-scripted interactive behaviors. Analysis based on sensory data and survey data shows that adaptable behaviors within an expert-designed action space can achieve higher engagement and likeability.

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“…On the contrary, the repulsive forces are assigned to the obstacles that will move away the mobile robot. Those forces will drive the mobile robot toward the goal while avoiding the obstacles on its way [8].…”

Section: Introductionmentioning

confidence: 99%

Vortex Artificial Potential Field for Mobile Robot Path Planning

Nasuha

Priambodo

Pratama

2022

J. Phys.: Conf. Ser.

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Artificial Potential Field (APF) is one of path planning strategies which offers a relatively low cost on computational. It has been implemented in many real-time applications. Unfortunately, it is quite susceptible to local minima problems. In this paper, we offer a scheme for escaping local minima by using vortex field. Based on the results and simulation, it can be verified that the vortex field prevails to navigate the path while escaping local minima.

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Unified environment-adaptive control of accompanying robots using artificial potential field

Cited by 8 publications

References 1 publication

Research on Design and Motion Control of a Considerate Guide Mobile Robot for Visually Impaired People

Research on Design and Motion Control of a Considerate Guide Mobile Robot for Visually Impaired People

Learning to Engage with Interactive Systems

Vortex Artificial Potential Field for Mobile Robot Path Planning

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