The availability of location information has become a key factor in today's communications systems allowing location based services. In outdoor scenarios, the mobile terminal position is obtained with high accuracy thanks to the global positioning system (GPS) or to the standalone cellular systems. However, the main problem of GPS and cellular systems resides in the indoor environment and in scenarios with deep shadowing effects where the satellite or cellular signals are broken. In this paper, we survey different technologies and methodologies for indoor and outdoor localization with an emphasis on indoor methodologies and concepts. Additionally, we discuss in this review different localization-based applications, where the location information is critical to estimate. Finally, a comprehensive discussion of the challenges in terms of accuracy, cost, complexity, security, scalability, etc. is given. The aim of this survey is to provide a comprehensive overview of existing efforts as well as auspicious and anticipated dimensions for future work in indoor localization techniques and applications.

Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications

Classical sensor-based approaches tend to constrain all the degrees of freedom of a robot during the execution of a task. In this paper, a new solution is proposed. The key idea is to divide the global full-constraining task into several subtasks, which can be applied or inactivated to take into account potential constraints of the environment. Far from any constraint, the robot moves according to the full task. When it comes closer to a configuration to avoid, a higher level controller removes one or several subtasks, and activates them again when the constraint is avoided. The last controller ensures the convergence at the global level by introducing some look-ahead capabilities when a local minimum is reached. The robot accomplishes the global task by automatically sequencing sensor-based tasks, obstacle avoidance, and short deliberative phases. In this paper, a complete solution to implement this idea is proposed, along with several experiments that prove the validity of this approach

https://hal.inria.fr/inria-00350593/document

Task Sequencing for High-Level Sensor-Based Control

Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.

Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges

This paper presents a novel two-level scheme for adaptive active visual servoing of a mobile robot equipped with a pan camera. In the lower level, the pan platform carrying an onboard camera is controlled to keep the reference points lying around the center of the image plane. On the higher level, a switched controller is utilized to drive the mobile robot to reach the desired configuration through image feature feedback. The designed active visual servoing system presents such advantages as follows: 1) a satisfactory solution for the field-of-view problem; 2) global high servoing efficiency; and 3) free of any complex pose estimation algorithm usually required for visual servoing systems. The performance of the active visual servoing system is proven by rigorous mathematical analysis. Both simulation and experimental results are provided to validate the effectiveness of the proposed active visual servoing method.

Adaptive Active Visual Servoing of Nonholonomic Mobile Robots

We propose new redundancy-based solutions to avoid robot joint limits of a manipulator. We use a control scheme based on the task function approach. We first recall the classical gradient projection approach and then present a far more efficient method that relies on the iterative computation of motion that does not affect the task achievement and ensures the avoidance problem. We apply this new method in a visual servoing application. We demonstrate the validity of the approach on various real experiments as well as on the control of a virtual humanoid.

/pdf/a-redundancy-based-iterative-approach-for-avoiding-joint-ufs8ffdgmo.pdf

A redundancy-based iterative approach for avoiding joint limits: application to visual servoing

Vision and RFID data fusion for tracking people in crowds by a mobile robot

Dynamical sequence of multi-sensor based tasks for mobile robots navigation

This paper deals with the tracking of persons in a human cluttered environment. It is performed by an active perception system, consisting of a camera mounted on a pan-tilt unit and a 360° RFID detection system which are embedded on a mobile robot. Particle filters enable the fusion of heterogeneous data into the proposal distribution from which the particles are sampled. The information provided by the tracker is then used to build sensor-based dedicated control laws in order to make the robot follow the RFID tagged person. Finally, experiments on our mobile robot are presented in order to highlight the relevance and complementarity of the developed perceptual functions.

/pdf/vision-and-rfid-based-person-tracking-in-crowds-from-a-637r14x23m.pdf

Vision and RFID-based person tracking in crowds from a mobile robot

Presents a controller for driving a mobile robot towards a target in a cluttered environment The proposed method combines visual servoing techniques allowing the target to be tracked, with an obstacle avoidance strategy based on the information provided by a 2D laser range sensor Simulation results are presented at the end of the paper

A controller to perform a visually guided tracking task in a cluttered environment

This paper presents a navigational framework which enables a robot to perform Long Range Navigation in the context of the Air-Cobot-Project in which a robot is used to execute an autonomous pre-flight inspection on an aircraft. The robot is equipped with Laser range finders and a mobile stereo camera system. The idea is to guide the robot to the pre-defined checkpoints using a Visual Servoing controller based on video data, while avoiding static and moving obstacles. The contribution of the paper is an avoidance technique derived from the spiral flight path of insects applied to the Laser range data. Simulation results validate the whole approach.

/pdf/a-navigational-framework-combining-visual-servoing-and-4h8oihgxzu.pdf

Viviane Cadenat

Papers

Vision and RFID data fusion for tracking people in crowds by a mobile robot

Dynamical sequence of multi-sensor based tasks for mobile robots navigation

Vision and RFID-based person tracking in crowds from a mobile robot

A controller to perform a visually guided tracking task in a cluttered environment

A navigational framework combining Visual Servoing and spiral obstacle avoidance techniques