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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Roxana M. Agrigoroaie Adriana Tapus Robotics and Computer Vision Lab U21S ENSTA Pari sTech Université Paris-Saclay Palaiseau France

ISBN: (纸本)9781467383707

My PhD research aims to develop a general framework for a behavior control architecture that will provide customized interaction between the robot and an elderly individual suffering from mild cognitive impairment (MCI). This framework will enable the robot to learn from past events and to adapt its behavior to the specific needs of the person that it interacts with. For this purpose, models will be created for both verbal and non-verbal communication. The user profile (e.g., personality, cognitive disability level, emotional internal states, preferences) will provide the input based on which the robot will adapt its behavior.

关键词： Robots Senior citizens Conferences Lifting equipment Games Testing Human-robot interaction

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Planning feasible and safe paths online for autonomous underwater vehicles in unknown environments

Planning feasible and safe paths online for autonomous under...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Juan David Hernandez Mark Moll Eduard Vidal Marc Carreras Lydia E. Kavraki Underwater Vision and Robotics Research Center (CIRS) University of Girona Spain Department of Computer Science at Rice University Houston TX USA

ISBN: (纸本)9781509037636

We present a framework for planning collision-free and safe paths online for autonomous underwater vehicles (AUVs) in unknown environments. We build up on our previous work and propose an improved approach. While preserving its main modules (mapping, planning and mission handler), the framework now considers motion constraints to plan feasible paths, i.e., those that meet vehicle's motion capabilities. The new framework also incorporates a risk function to avoid navigating close to nearby obstacles, and reuses the last best known solution to eliminate time-consuming pruning routines. To evaluate this approach, we use the Sparus II AUV, a torpedo-shaped vehicle performing autonomous missions in a 2-dimensional workspace. We validate the framework's new features by solving tasks in both simulation and real-world in-water trials and comparing results with our previous approach.

关键词： Planning Navigation Path planning Underwater autonomous vehicles Differential equations Vehicle dynamics

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A flexible and dynamic mission planning architecture for UAV swarm coordination

A flexible and dynamic mission planning architecture for UAV...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Carlos Sampedro Hriday Bavle Jose Luis Sanchez-Lopez Ramon A. Suárez Fernández Alejandro Rodríguez-Ramos Martin Molina Pascual Campoy Computer Vision Group Center for Automation and Robotics (UPM-CSIC) Madrid Spain Department of Artificial Intelligence Technical University of Madrid (UPM) Spain

ISBN: (纸本)9781467393355

In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multi-agent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.

关键词： computer architecture Planning Robot kinematics Monitoring Real-time systems Trajectory

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Model predictive position/force control of an anthropomorphic robotic arm

Model predictive position/force control of an anthropomorphi...

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2015 IEEE International Conference on Industrial Technology, ICIT 2015

作者： De La Casa Cardenas, J. Garcia, A. Sanchez Martinez, S. Satorres Garcia, J. Gamez Ortega, J. Gomez Group of Robotics Automation and Computer Vision University of Jaén Germany

ISBN: (纸本)9781479978007

When a robotic manipulator executes a task in restricted and unknown environments, it is necessary to implement a position/force control in free space and constrained space. In classic controllers, position/force control may be carried out by means a controller switching, once the contact point has been reached. In this paper, a new position/force predictive controller for an anthropomorphic robotic arm is proposed. This work proposes an unique control law for controlling both variables (position or force). In a model predictive framework, where several goals have to be reached, it is known that cost function includes several parameters (weights) whose modification allows to prioritize goals to achieve. This fact has been taken into account to set up the controller. The proposed control law is validated by experiments involving a 7-dof anthropomorphic robotic arm executing a trajectory tracking task in a restricted environment. As experimental results show, it is possible to control position and force by adjusting controller weights. © 2015 IEEE.

关键词： Robotic arms

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Improving multi-view object recognition by detecting changes in point clouds

Improving multi-view object recognition by detecting changes...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Martin Velas Thomas Fäulhammer Michal Spanel Michael Zillich Markus Vincze Department of Computer Graphics and Multimedia Brno University of Technology Czech Republic Vision4Robotics group (ACIN) Vienna University of Technology Austria

This paper proposes the use of change detection in a multi-view object recognition system in order to improve its flexibility and effectiveness in dynamic environments. Multi-view recognition approaches are essential to overcome problems related to clutter, occlusion or camera noise, but the existing systems usually assume a static environment. The presence of dynamic objects raises another issue - the inconsistencies introduced to the internal scene model. We show that by incorporating the change detection and correction of the inherent scene inconsistencies, we reduce false positive detections by 70% in average for moving objects when tested on the publicly available TUW dataset. To reduce time required for verifying a large set of accumulated object pose hypotheses, we further integrate a clustering approach into the original multi-view object recognition system and show that this reduces computation time by 16%.

关键词： Three-dimensional displays Object recognition Feature extraction Cameras Computational modeling Sensors Pipelines

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Free-floating panel intervention by means of learning by demonstration

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IFAC-PapersOnLine 2015年第2期28卷 38-43页

作者： Carrera, Arnau Palomeras, Narcís Hurtós, Natàlia Carreras, Marc Computer Vision and Robotics Institute Centre d'Investigació en Robòtica Submarina Universitat de Girona Girona17003 Spain

Recent efforts in the field of intervention-autonomous underwater vehicles (I-AUVs) have started to show promising results in simple manipulation tasks. However, there is still a long way to go to reach the complexity of the tasks carried out by ROV pilots. This paper proposes an intervention framework based on Learning by Demonstration (LbD) techniques in order to easily acquire the manipulation skills of a pilot and be able to reproduce similar tasks autonomously. We describe the learning algorithm as well as its interplay with the rest of the modules (navigation, perception, control) that take part in the proposed framework. We show results on a free-floating valve turning task, using Girona 500 AUV equipped with a manipulator, a passive gripper, a force/torque sensor, a camera and a haptic device to perform the demonstrations. Obtained results show the feasibility of the LbD algorithm to perform autonomous intervention even under the presence of perturbations. © 2015, IF AG (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Autonomous underwater vehicles Demonstrations Learning algorithms Learning systems Remotely operated vehicles Autonomous interventions Autonomous underwater vehicles (AUV) Free floating manipulation Human Machine Interface Learning by demonstration

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Pose estimation for underwater vehicles using light beacons

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IFAC-PapersOnLine 2015年第2期28卷 70-75页

作者： Gracias, Nuno Bosch, Josep Karim, Mohammad Ehsanul Computer Vision and Robotics Institute Centre d'Investigació en Robòtica Submarina Universitat de Girona Girona17003 Spain

This paper presents an approach for estimating the relative location and orientation between two or more underwater vehicles operating in tight formation. One of the vehicles is equipped with a camera of wide field of view. The other vehicle(s) are equipped with active light markers to enable the use of computer vision for pose estimation. The pose estimation addresses two scenarios, which are both important from the operational point of view. The first pertains to the availability of an acoustic communication channel which allows for exchanging attitude data and acoustic ranging, and use it in the pose estimation procedure. The second corresponds to the exclusive use of a set of 4 or more optical beacons with no acoustic information exchange, which is a capability that has not been yet proposed nor demonstrated in underwater vehicles. The contributions can be summarize as (1) a novel method of estimating the pose of an autonomous underwater vehicle using light beacons and other sensors when available, (2) an automated marker configuration analysis approach. Performance of the pose estimation approach is evaluated using synthetic and real data. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Underwater acoustics Autonomous underwater vehicles computer vision Navigation Optical systems Visual servoing Active markers Cooperative navigations Formation control Relative localization Robot navigation Underwater vehicles

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Object proposal using 3D point cloud for DRC-HUBO+

Object proposal using 3D point cloud for DRC-HUBO+

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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Seunghak Shin Inwook Shim Jiyung Jung Yunsu Bok Jun-Ho Oh In So Kweon Dep. of EE Robotics and Computer Vision Labortory Daejeon Korea Naver Labs Seongnam Korea Dep. of ME Humanoid Research Center Daejeon Korea

ISBN: (纸本)9781509037636

We present an object proposal method which utilizes the 3D data obtained from a depth sensor as well as the color information of images. Our object proposal method is designed to improve the performance of the object detection for a mobile robot equipped with a camera and a laser scanner. Compared to traditional object proposal methods using only 2D images, the proposed method provides much less number of candidate windows for object detection. We show less than 100 object proposal windows per image using the proposed method result in high recall tested on the public dataset. Our method presents object proposals in 3D space as well as in 2D image thus it can further be applied to following tasks for mobile robots such as 3D location and pose estimation of the target object after successful object detection. We validate our method using the real-world object detection dataset for outdoor mobile robots captured during the DRC Finals 2015 and the public dataset for comparison with the previous methods.

关键词： Proposals Three-dimensional displays Robot sensing systems Cameras Object detection Image color analysis

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Natural User Interfaces for Human-Drone Multi-Modal Interaction

Natural User Interfaces for Human-Drone Multi-Modal Interact...

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International Conference on Unmanned Aircraft Systems

作者： Ramón A. Suárez Fernández Jose Luis Sanchez-Lopez Carlos Sampedro Hriday Bavle Martin Molina Pascual Campoy Computer Vision Group Centre for Automation and Robotics CSIC-UPM (Spain)

ISBN: (纸本)9781467393355

Personal drones are becoming part of every day life. To fully integrate them into society, it is crucial to design safe and intuitive ways to interact with these aerial systems. The recent advances on User-Centered Design (UCD) applied to Natural User Interfaces (NUIs) intend to make use of human innate features, such as speech, gestures and vision to interact with technology in the way humans would with one another. In this paper, a Graphical User Interface (GUI) and several NUI methods are studied and implemented, along with computer vision techniques, in a single software framework for aerial robotics called Aerostack which allows for intuitive and natural human-quadrotor interaction in indoor GPS-denied environments. These strategies include speech, body position, hand gesture and visual marker interactions used to directly command tasks to the drone. The NUIs presented are based on devices like the Leap Motion Controller, microphones and small size monocular on-board cameras which are unnoticeable to the user. Thanks to this UCD perspective, the users can choose the most intuitive and effective type of interaction for their application. Additionally, the strategies proposed allow for multi-modal interaction between multiple users and the drone by being able to integrate several of these interfaces in one single application as is shown in various real flight experiments performed with non-expert users.

关键词： UCD Natural User

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A real-time supervised learning approach for sky segmentation onboard unmanned aerial vehicles

A real-time supervised learning approach for sky segmentatio...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Adrian Carrio Carlos Sampedro Changhong Fu Jean-François Collumeau Pascual Campoy Computer Vision Group Center for Automation and Robotics (UPM-CSIC) Madrid Spain School of Mechanical and Aerospace Engineering and ST Engineering-NTU Corp Laboratory Nanyang Technological University Singapore

vision-based sky segmentation and horizon line detection can be extremely useful to perform important tasks onboard Unmanned Aerial Vehicles (UAVs), such as pose estimation and collision avoidance. Most of the existing vision-based solutions use traditional image processing methods to identify the horizon line. This results in good overall accuracy and fast computation times. However, difficult environmental conditions such as a foggy or cloudy skies hinder correct sky segmentation. This paper proposes a solution for sky segmentation in RGB images using a supervised Machine Learning approach by first splitting the image into fixed-size patches, extracting and classifying color descriptors for each patch and performing a final post-processing stage to improve segmentation quality. A method for automatic horizon line detection is also proposed. The performance of our approach was evaluated on flight images captured onboard UAVs, achieving performance accuracies above 93% at real-time frame rates.

关键词： Image color analysis Image segmentation Aircraft Image edge detection Histograms Real-time systems Unmanned aerial vehicles

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