IDVD-based trajectory generator for autonomous underwater docking operations

2017 ◽  
Vol 92 ◽  
pp. 12-29 ◽  
Author(s):  
A.M. Yazdani ◽  
K. Sammut ◽  
O.A. Yakimenko ◽  
A. Lammas ◽  
Y. Tang ◽  
...  
Keyword(s):  
Underwater Docking ◽  
Trajectory Generator

scholarly journals Design of Hesitation Gestures for Nonverbal Human-Robot Negotiation of Conflicts

2021 ◽  
Vol 10 (3) ◽  
pp. 1-25
Author(s):  
Ajung Moon ◽  
Maneezhay Hashmi ◽  
H. F. Machiel Van Der Loos ◽  
Elizabeth A. Croft ◽  
Aude Billard
Keyword(s):  
Nonverbal Communication ◽  
Human Subjects ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Resource Conflicts ◽  
Conflict Situations ◽  
Interaction Experiment ◽  
Characteristic Features ◽  
Trajectory Generator ◽  
Positive Results

When the question of who should get access to a communal resource first is uncertain, people often negotiate via nonverbal communication to resolve the conflict. What should a robot be programmed to do when such conflicts arise in Human-Robot Interaction? The answer to this question varies depending on the context of the situation. Learning from how humans use hesitation gestures to negotiate a solution in such conflict situations, we present a human-inspired design of nonverbal hesitation gestures that can be used for Human-Robot Negotiation. We extracted characteristic features of such negotiative hesitations humans use, and subsequently designed a trajectory generator (Negotiative Hesitation Generator) that can re-create the features in robot responses to conflicts. Our human-subjects experiment demonstrates the efficacy of the designed robot behaviour against non-negotiative stopping behaviour of a robot. With positive results from our human-robot interaction experiment, we provide a validated trajectory generator with which one can explore the dynamics of human-robot nonverbal negotiation of resource conflicts.

Analysis of Hydrodynamic Characteristics in the Process of Autonomous Underwater Vehicle Docking

2015 ◽  
Author(s):  
Xiaoxu Du ◽  
Huan Wang
Keyword(s):  
Drag Coefficient ◽  
Autonomous Underwater Vehicle ◽  
Simple Algorithm ◽  
Underwater Vehicle ◽  
Navier Stokes ◽  
Hydrodynamic Characteristics ◽  
Successful Operation ◽  
Underwater Docking ◽  
Computational Fluid Dynamics Cfd ◽  
Volume Method

The successful operation of an Autonomous Underwater Vehicle (AUV) requires the capability to return to a dock. A number of underwater docking technologies have been proposed and tested in the past. The docking allows the AUV to recharge its batteries, download data and upload new instructions, which is helpful to improve the working time and efficiency. During the underwater docking process, unsteady hydrodynamic interference occurs between the docking device and an AUV. To ensure a successful docking, it is very important that the underwater docking hydrodynamics of AUV is understood. In this paper, numerical simulations based on the computational fluid dynamics (CFD) solutions were carried out for a 1.85m long AUV with maximum 0.2 m in diameter during the docking process. The two-dimensional AUV model without fin and rudder was used in the simulation. The mathematical model based on the Reynolds-averaged Navier-Stokes (RANS) equations was established. The finite volume method (FVM) and the dynamic structured mesh technique were used. SIMPLE algorithm and the k-ε turbulence model in the Descartes coordinates were also adopted. The hydrodynamics characteristics of different docking states were analyzed, such as the different docking velocity, the docking device including baffle or not. The drag coefficients of AUV in the process of docking were computed for various docking conditions, i.e., the AUV moving into the docking in the speed of 1m/s, 2m/s, 5m/s. The results indicate that the drag coefficient increases slowly in the process of AUV getting close to the docking device. When the AUV moves into the docking device, the drag coefficient increases rapidly. Then the drag coefficient decreases rapidly. The drag coefficient decreases with the increase of velocity when AUV enters the docking device. It was also found that the drag coefficient can be effectively reduced by dislodging the baffle of docking device.

Path Following System for Cooperative Mobile Robots

2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu
Keyword(s):  
Artificial Intelligence ◽  
Mobile Robots ◽  
Path Following ◽  
Path Generation ◽  
Cooperative Robots ◽  
Generation System ◽  
Robot Systems ◽  
Simulation Results ◽  
Trajectory Generator

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.

DISCRETE SECOND ORDER TRAJECTORY GENERATOR WITH NONLINEAR CONSTRAINTS

2005 ◽  
Vol 38 (1) ◽  
pp. 200-205
Author(s):  
Riccardo Morselli ◽  
Roberto Zanasi ◽  
Stefano Stramigioli
Keyword(s):  
Second Order ◽  
Nonlinear Constraints ◽  
Trajectory Generator
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