Socially Acceptable Navigation of People with Multi-robot Teams

Batista, Murillo Rehder; Macharet, Douglas G.; Romero, Roseli Aparecida Francelin

doi:10.1007/s10846-019-01080-4

Cited by 8 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several measures of navigation performance had been previously used to assess the performance of machine-learning-based methods for social navigation behaviours in autonomous robots [66][67][68][69][70][71][72]. However, these studies focused on algorithms that automatically plan a socially acceptable path without involvement of a human operator.…”

Section: Plos Onementioning

confidence: 99%

How automatic speed control based on distance affects user behaviours in telepresence robot navigation within dense conference-like environments

et al. 2020

View full text Add to dashboard Cite

Telepresence robots allow users to be spatially and socially present in remote environments. Yet, it can be challenging to remotely operate telepresence robots, especially in dense environments such as academic conferences or workplaces. In this paper, we primarily focus on the effect that a speed control method, which automatically slows the telepresence robot down when getting closer to obstacles, has on user behaviors. In our first user study, participants drove the robot through a static obstacle course with narrow sections. Results indicate that the automatic speed control method significantly decreases the number of collisions. For the second study we designed a more naturalistic, conference-like experimental environment with tasks that require social interaction, and collected subjective responses from the participants when they were asked to navigate through the environment. While about half of the participants preferred automatic speed control because it allowed for smoother and safer navigation, others did not want to be influenced by an automatic mechanism. Overall, the results suggest that automatic speed control simplifies the user interface for telepresence robots in static dense environments, but should be considered as optionally available, especially in situations involving social interactions.

show abstract

Section: Plos Onementioning

confidence: 99%

How automatic speed control based on distance affects user behaviours in telepresence robot navigation within dense conference-like environments

et al. 2020

View full text Add to dashboard Cite

show abstract

“…For example, in [ 16 ] the authors have developed an algorithm for precise mobile robot path tracking in off road terrain that has been updated by using the tracking error dynamics. Another study on social navigation considering a human and a robot team has been presented by the authors in [ 17 ] in which they considered social aspects when introducing various navigation strategies and compared in simulated environment by terms as the average number of robots invading the personal space and the number of robots to the person’s side, with two of them using Asymmetric Gaussian Functions (AGFs) as the person’s social zone model. Ribeiro and Conceição in [ 18 ] presented a Nonlinear Model Predictive Control depending on the image plane where simplified visual features are extracted from the path to be followed.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

Batayneh

Aburmaileh

2020

Sensors

View full text Add to dashboard Cite

The last decade observed a significant research effort directed towards maneuverability and safety of mobile robots such as smart wheelchairs. The conventional electric wheelchair can be equipped with motorized omnidirectional wheels and several sensors serving as inputs for the controller to achieve smooth, safe, and reliable maneuverability. This work uses the decentralized algorithm to control the motion of omnidirectional wheelchairs. In the body frame of the omnidirectional wheeled wheelchair there are three separated independent components of motion including rotational motion, horizontal motion, and vertical motion, which can be controlled separately. So, each component can have its different sub-controller with a minimum tracking error. The present work aims to enhance the mobility of wheelchair users by utilizing an application to control the motion of their attained/unattained smart wheelchairs, especially in narrow places and at hard detours such as 90˚ corners and U-turns, which improves the quality of life of disabled users by facilitating their wheelchairs’ maneuverability. Two approaches of artificial intelligent-based controllers (PD-Fuzzy-P and GA-PID controllers) are designed to optimally enhance the maneuverability of the system. MATLAB software is used to simulate the system and calculate the Mean Error (ME) and Mean Square Error (MSE) for various scenarios in both approaches, the results showed that the PD-Fuzzy-P controller has a faster convergence in trajectory tracking than the GA-PID controller. Therefore, the proposed system can find its application in many areas including transporting locomotor-based disabled individuals and geriatric people as well as automated guided vehicles.

show abstract

A Multimodal Path Planning Approach to Human Robot Interaction Based on Integrating Action Modeling

Kawasaki

Yorozu

Takahashi

et al. 2020

J Intell Robot Syst

View full text Add to dashboard Cite

Socially Acceptable Navigation of People with Multi-robot Teams

Cited by 8 publications

References 30 publications

How automatic speed control based on distance affects user behaviours in telepresence robot navigation within dense conference-like environments

How automatic speed control based on distance affects user behaviours in telepresence robot navigation within dense conference-like environments

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

A Multimodal Path Planning Approach to Human Robot Interaction Based on Integrating Action Modeling

Contact Info

Product

Resources

About