Navigation and Control of Mobile Robot Using Sensor Fusion

Non

Control and Model-Aided Inertial Navigation of a Nonholonomic Vehicle

International audienceThe present work deals with the control and localization problem of wheeled-mobile robots with nonholonomic constraints. In the proposed method a simple nonlinear control law, composed of a position and heading direction controller, is designed to asymptotically stabilize the position error. The control law takes into account the constraints on the control signals in order to avoid saturation of the actuators. Furthermore, this paper considers a method of using the dynamic vehicle model and vehicle's nonholonomic constraints in order to aid position and attitude estimates provided by an Inertial Navigation System (INS). It is shown that dynamic model and vehicle's nonholonomic constraints can reduce the error growth in robot position estimates. Simulations are included to confirm the effectiveness of the proposed scheme

Sensor Fusion of Raw GPS Measurements for Autonomous Vehicle Localization

We developed a software able to establish geometric constraints for a localization problem from raw GPS measurements. Then we integrated it in Wolf, a software framework for managing SLAM, enriching its sensor fusion capabilities. In the end we tested the sensor fusion between raw GPS and odometr

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Event based localization in Ackermann steering limited resource mobile robots

“© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”This paper presents a local sensor fusion technique with an event-based global position correction to improve the localization of a mobile robot with limited computational resources. The proposed algorithms use a modified Kalman filter and a new local dynamic model of an Ackermann steering mobile robot. It has a similar performance but faster execution when compared to more complex fusion schemes, allowing its implementation inside the robot. As a global sensor, an event-based position correction is implemented using the Kalman filter error covariance and the position measurement obtained from a zenithal camera. The solution is tested during a long walk with different trajectories using a LEGO Mindstorm NXT robot.This work was supported by FEDER-CICYT projects with references DPI2011-28507-C02-01 and DPI2010-20814-C02-02, financed by the Ministerio de Ciencia e Innovacion (Spain). This work was also supported by the University of Costa Rica.Marín, L.; Vallés Miquel, M.; Soriano Vigueras, Á.; Valera Fernández, Á.; Albertos Pérez, P. (2014). Event based localization in Ackermann steering limited resource mobile robots. IEEE/ASME Transactions on Mechatronics. 19(4):1171-1182. doi:10.1109/TMECH.2013.2277271S1171118219

Ultra-wideband time of flight based localization system and odometry fusion for a scanning 3 DoF magnetic field autonomous robot

Solving the robot localization problem is one of the most necessary requirements for autonomous robots. Several methodologies can be used to determine its location as accurately as possible. What makes this difficult is the existence of uncertainty in the sensing of the robot. The uncertain information needs to be combined in an optimal way. This paper stresses a Kalman filter to combine information from the odometry and Ultra Wide Band Time of Flight distance modules, which lacks the orientation. The proposed system validated in a real developed platform performs the fusion task which outputs position and orientation of the robot. It is used to localize the robot and make a 3 DoF scanning of magnetic field in a room. Other examples can be pointed out with the same localization techniques in service and industrial autonomous robots.Project “TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020” is financed by the North Portugal Regional Operational. Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF). This work is also financed by the ERDF European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the FCT Funda¸cao para a Ciˆencia e a Tecnologia (Portuguese Foundation for Science and Technology) within project POCI-01-0145-FEDER-006961.info:eu-repo/semantics/publishedVersio