Robotics

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Open AccessArticle

A Computational Model of Human-Robot Spatial Interactions Based on a Qualitative Trajectory Calculus

by Christian Dondrup, Nicola Bellotto, Marc Hanheide, Kerstin Eder and Ute Leonards

Robotics 2015, 4(1), 63-102; https://doi.org/10.3390/robotics4010063 - 23 Mar 2015

Cited by 19 | Viewed by 9967

In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI) using a well-established Qualitative Trajectory Calculus (QTC) to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to [...] Read more.

In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI) using a well-established Qualitative Trajectory Calculus (QTC) to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model. Full article

(This article belongs to the Special Issue Representations and Reasoning for Robotics)

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666 KiB

Open AccessArticle

An Application of Screw Theory to the Jerk Analysis of a Two-Degrees-of-Freedom Parallel Wrist

by Jaime Gallardo-Alvarado, Ramón Rodríguez-Castro, Martín Caudillo-Ramírez and Luciano Pérez-González

Robotics 2015, 4(1), 50-62; https://doi.org/10.3390/robotics4010050 - 10 Mar 2015

Cited by 2 | Viewed by 7797

Abstract

In this work the velocity, acceleration, and jerk analyses of a two-degrees-of-freedom parallel wrist are approached by means of the theory of screws. For the sake of completeness, the finite kinematics of the manipulator is also investigated. As far as the authors are [...] Read more.

In this work the velocity, acceleration, and jerk analyses of a two-degrees-of-freedom parallel wrist are approached by means of the theory of screws. For the sake of completeness, the finite kinematics of the manipulator is also investigated. As far as the authors are aware, the equation of jerk in screw form of the robot at hand is introduced by the first time in this contribution. In order to exemplify the method, a case study is included. The numerical example is verified with the aid of commercially available software. Full article

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Open AccessArticle

Development of an Effective Docking System for Modular Mobile Self-Reconfigurable Robots Using Extended Kalman Filter and Particle Filter

by Peter Won, Mohammad Biglarbegian and William Melek

Robotics 2015, 4(1), 25-49; https://doi.org/10.3390/robotics4010025 - 12 Feb 2015

Cited by 13 | Viewed by 9110

Abstract

This paper presents an autonomous docking system with novel integrated algorithms for mobile self-reconfigurable robots equipped with inexpensive sensors. A novel docking algorithm was developed to determine the initial distance and orientation of the two modules, and sensor models were established through experiments. [...] Read more.

This paper presents an autonomous docking system with novel integrated algorithms for mobile self-reconfigurable robots equipped with inexpensive sensors. A novel docking algorithm was developed to determine the initial distance and orientation of the two modules, and sensor models were established through experiments. Both Extended Kalman filter (EKF) and particle filter (PF) were deployed to fuse the measurements from IR and encoders and provide accurate estimates of orientation and distance. Simulation experiments were carried out first and then real experiments were conducted to verify the feasibility and good performance of the proposed docking algorithm and system. The proposed system provides a robust and reliable docking solution using low cost sensors. Full article

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Open AccessEditorial

Acknowledgement to Reviewers of Robotics in 2014

by Robotics Editorial Office

Robotics 2015, 4(1), 23-24; https://doi.org/10.3390/robotics4010023 - 08 Jan 2015

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Abstract

The editors of Robotics would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...] Full article

2829 KiB

Open AccessArticle

Vision-Based Cooperative Pose Estimation for Localization in Multi-Robot Systems Equipped with RGB-D Cameras

by Xiaoqin Wang, Y. Ahmet Şekercioğlu and Tom Drummond

Robotics 2015, 4(1), 1-22; https://doi.org/10.3390/robotics4010001 - 26 Dec 2014

Cited by 15 | Viewed by 8086

Abstract

We present a new vision based cooperative pose estimation scheme for systems of mobile robots equipped with RGB-D cameras. We first model a multi-robot system as an edge-weighted graph. Then, based on this model, and by using the real-time color and depth data, [...] Read more.

We present a new vision based cooperative pose estimation scheme for systems of mobile robots equipped with RGB-D cameras. We first model a multi-robot system as an edge-weighted graph. Then, based on this model, and by using the real-time color and depth data, the robots with shared field-of-views estimate their relative poses in pairwise. The system does not need the existence of a single common view shared by all robots, and it works in 3D scenes without any specific calibration pattern or landmark. The proposed scheme distributes working loads evenly in the system, hence it is scalable and the computing power of the participating robots is efficiently used. The performance and robustness were analyzed both on synthetic and experimental data in different environments over a range of system configurations with varying number of robots and poses. Full article

(This article belongs to the Special Issue Coordination of Robotic Systems)

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Robotics, Volume 4, Issue 1 (March 2015) – 5 articles , Pages 1-102

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