Vision-Based Localization Algorithm Based on Landmark Matching, Triangulation, Reconstruction, and Comparison

Many generic position-estimation algorithms are vulnerable to ambiguity introduced by nonunique landmarks. Also, the available high-dimensional image data is not fully used when these techniques are extended to vision-based localization. This paper presents the landmark matching, triangulation, reconstruction, and comparison (LTRC) global localization algorithm, which is reasonably immune to ambiguous landmark matches. It extracts natural landmarks for the (rough) matching stage before generating the list of possible position estimates through triangulation. Reconstruction and comparison then rank the possible estimates. The LTRC algorithm has been implemented using an interpreted language, onto a robot equipped with a panoramic vision system. Empirical data shows remarkable improvement in accuracy when compared with the established random sample consensus method. LTRC is also robust against inaccurate map data

Detection & isolation of sensor and actuator additive faults in a 4-mecanum wheeled mobile robot (4-MWMR)

International audienceIn this paper, the fault detection and isolation problem regarding actuation and sensing of a 4-mecanum wheeled mobile robot (4-MWMR) is studied. The challenge with respect to the current state of the art lies in detecting and distinguishing wheel sensor from wheel actuator additive faults for this kind of robots. An approach based on generating residuals is proposed. Sensor faults isolation is based on simply analyzing residual signatures which are different under each sensor fault. Due to omni-move properties, actuator faults are, however, more difficult to be isolated. More residual characteristics must be taken into consideration to achieve the isolation

Robusni adaptivni observer temeljen na algoritmu za kooperaciju mobilnih robota s više kotača

Wheeled mobile robots (WMRs) are of great importance. Therefore, it is necessary to make sure that they are not defected. But, in case of failures, the diagnosis task is very important to predict then solve the problem. The most useful techniques in diagnosis are observers which are based on the observability of the monitored system that is not usually ensured by WMR. Thus, to overcome this drawback, an intelligent cooperative diagnosis algorithm is proposed and tested for a group of mobile robots. The diagnosis algorithm is based on robust adaptive unknown input observer applied on unobservable robot. The local non-observability of each robot is solved by cooperative communication. The idea consists on considering all WMRs as a Large Scale System (LSS) even these robots may have not common task. Then, the LSS is decomposed into subsystems that everyone refers to each robot communicating with its neighbors. Next, a design of cooperative interconnected systems is studied to reassure the new condition of observability. Besides, Fast Adaptive Fault Estimation (FAFE) algorithm is proposed to improve the performances of the fault estimation. Finally, to illustrate the efficiency of the proposed algorithm, a model of three-wheel omnidirectional mobile robot is presented.Mobilni roboti na kotačima od velike su važnosti. Stoga, nužno je osigurati da ne odlutaju. U slučaju kvara važna je dijagnoza kako bi se predvidio i onda riješio problem. Najkorisnije dijagnostičke tehnike su observeri koji se zasnivaju na osmotrivosti nadgledanih sustava koja kod mobilnih robota na kotačima najčešće nije osigurana. Stoga, kako bi se nadišao ovaj problem, koristi se inteligentan algoritam za kooperativnu dijagnozu i testira se na grupi mobilnih robota. Dijagnostički algoritam zasniva se na robusnom adaptivnom observeru s nepoznatim ulazom koji je primijenjen na neosmotrivom robotu. Lokalna neosmotrivost svakog robota riješena je koopreativnom komunikacijom. Ideja je da se svi mobilni roboti promatraju kao sustav velikih razmjera iako roboti nemaju isti zadatak. Sustav velikih razmjera se tada rastavlja na podsutave tako da se svaki odnosi na jednog robota koji komunicira sa svojim susjedima. Zatim se proučava dizajn kooperativnih povezanih sustava kako bi se osigurali uvjeti za osmotrivost. Dodatno, predlaže se korištenje brze adaptivne estimacije pogreške kako bi se poboljšala estimacije pogreške. Konačno, prikazan je model višesmjernog mobilnog robota na tri kotača kako bi se ilustrirala učinkovitost predloženog algoritma

MOMA: Visual Mobile Marker Odometry

In this paper, we present a cooperative odometry scheme based on the detection of mobile markers in line with the idea of cooperative positioning for multiple robots [1]. To this end, we introduce a simple optimization scheme that realizes visual mobile marker odometry via accurate fixed marker-based camera positioning and analyse the characteristics of errors inherent to the method compared to classical fixed marker-based navigation and visual odometry. In addition, we provide a specific UAV-UGV configuration that allows for continuous movements of the UAV without doing stops and a minimal caterpillar-like configuration that works with one UGV alone. Finally, we present a real-world implementation and evaluation for the proposed UAV-UGV configuration

Vision-based methods for state estimation and control of robotic systems with application to mobile and surgical robots

For autonomous systems that need to perceive the surrounding environment for the accomplishment of a given task, vision is a highly informative exteroceptive sensory source. When gathering information from the available sensors, in fact, the richness of visual data allows to provide a complete description of the environment, collecting geometrical and semantic information (e.g., object pose, distances, shapes, colors, lights). The huge amount of collected data allows to consider both methods exploiting the totality of the data (dense approaches), or a reduced set obtained from feature extraction procedures (sparse approaches). This manuscript presents dense and sparse vision-based methods for control and sensing of robotic systems. First, a safe navigation scheme for mobile robots, moving in unknown environments populated by obstacles, is presented. For this task, dense visual information is used to perceive the environment (i.e., detect ground plane and obstacles) and, in combination with other sensory sources, provide an estimation of the robot motion with a linear observer. On the other hand, sparse visual data are extrapolated in terms of geometric primitives, in order to implement a visual servoing control scheme satisfying proper navigation behaviours. This controller relies on visual estimated information and is designed in order to guarantee safety during navigation. In addition, redundant structures are taken into account to re-arrange the internal configuration of the robot and reduce its encumbrance when the workspace is highly cluttered. Vision-based estimation methods are relevant also in other contexts. In the field of surgical robotics, having reliable data about unmeasurable quantities is of great importance and critical at the same time. In this manuscript, we present a Kalman-based observer to estimate the 3D pose of a suturing needle held by a surgical manipulator for robot-assisted suturing. The method exploits images acquired by the endoscope of the robot platform to extrapolate relevant geometrical information and get projected measurements of the tool pose. This method has also been validated with a novel simulator designed for the da Vinci robotic platform, with the purpose to ease interfacing and employment in ideal conditions for testing and validation. The Kalman-based observers mentioned above are classical passive estimators, whose system inputs used to produce the proper estimation are theoretically arbitrary. This does not provide any possibility to actively adapt input trajectories in order to optimize specific requirements on the performance of the estimation. For this purpose, active estimation paradigm is introduced and some related strategies are presented. More specifically, a novel active sensing algorithm employing visual dense information is described for a typical Structure-from-Motion (SfM) problem. The algorithm generates an optimal estimation of a scene observed by a moving camera, while minimizing the maximum uncertainty of the estimation. This approach can be applied to any robotic platforms and has been validated with a manipulator arm equipped with a monocular camera

A fault-hiding approach for the switching quasi-LPV fault-tolerant control of a four-wheeled omnidirectional mobile robot

This paper proposes a reference model approach for the trajectory tracking of a four-wheeled omnidirectional mobile robot. In particular, the error model is brought to a quasi-linear-parameter-varying (LPV) form suitable for designing an error-feedback controller. It is shown that, if polytopic techniques are used to reduce the number of constraints from infinite to finite, a solution within the standard LPV framework could not exist due to a singularity that appears in the possible values of the input matrix. Adding a switching component to the controller allows solving this problem. Moreover, a switching LPV virtual actuator is added to the control loop in order to obtain fault tolerance within the fault-hiding paradigm, keeping the stability and some desired performances under the effect of actuator faults without the need of retuning the nominal controller. The effectiveness of the proposed approach is shown and proved through simulation and experimental results.This work has been funded by the Spanish MINECO through the project CYCYT SHERECS (ref. DPI2011-26243), by the European Commission through contract i-Sense (ref. FP7-ICT-2009-6-270428), by AGAUR through the contracts FI-DGR 2013 (ref. 2013FIB00218) and FI-DGR 2014 (ref. 2014FI B1 00172) and by the DGR of Generalitat de Catalunya (SAC group Ref. 2014/SGR/374).Peer Reviewe

An Omnidirectional Aerial Platform for Multi-Robot Manipulation

The objectives of this work were the modeling, control and prototyping of a new fully-actuated aerial platform. Commonly, the multirotor aerial platforms are under-actuated vehicles, since the total propellers thrust can not be directed in every direction without inferring a vehicle body rotation. The most common fully-actuated aerial platforms have tilted or tilting rotors that amplify the aerodynamic perturbations between the propellers, reducing the efficiency and the provided thrust. In order to overcome this limitation a novel platform, the ODQuad (OmniDirectional Quadrotor), has been proposed, which is composed by three main parts, the platform, the mobile and rotor frames, that are linked by means of two rotational joints, namely the roll and pitch joints. The ODQuad is able to orient the total thrust by moving only the propellers frame by means of the roll and pitch joints. Kinematic and dynamic models of the proposed multirotor have been derived using the Euler- Lagrange approach and a model-based controller has been designed. The latter is based on two control loops: an outer loop for vehicle position control and an inner one for vehicle orientation and roll-pitch joint control. The effectiveness of the controller has been tested by means of numerical simulations in the MATLAB c SimMechanics environment. In particular, tests in free motion and in object transportation tasks have been carried out. In the transportation task simulation, a momentum based observer is used to estimate the wrenches exchanged between the vehicle and the transported object. The ODQuad concept has been tested also in cooperative manipulation tasks. To this aim, a simulation model was considered, in which multiple ODQuads perform the manipulation of a bulky object with unknown inertial parameters which are identified in the first phase of the simulation. In order to reduce the mechanical stresses due to the manipulation and enhance the system robustness to the environment interactions, two admittance filters have been implemented: an external filter on the object motion and an internal one local for each multirotor. Finally, the prototyping process has been illustrated step by step. In particular, three CAD models have been designed. The ODQuad.01 has been used in the simulations and in a preliminary static analysis that investigated the torque values for a rough sizing of the roll-pitch joint actuators. Since in the ODQuad.01 the components specifications and the related manufacturing techniques have not been taken into account, a successive model, the ODQuad.02, has been designed. The ODQuad.02 design can be developed with aluminum or carbon fiber profiles and 3D printed parts, but each component must be custom manufactured. Finally, in order to shorten the prototype development time, the ODQuad.03 has been created, which includes some components of the off-the-shelf quadrotor Holybro X500 into a novel custom-built mechanical frame