Carlos Santos

Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors

Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance.

Odometry and laser scanner fusion based on a discrete extended kalman filter for robotic platooning guidance

This paper describes a relative localization system used to achieve the navigation of a convoy of robotic units in indoor environments. This positioning system is carried out fusing two sensorial sources: (a) an odometric system and (b) a laser scanner together with artificial landmarks located on top of the units. The laser source allows one to compensate the cumulative error inherent to dead-reckoning; whereas the odometry source provides less pose uncertainty in short trajectories. A discrete Extended Kalman Filter, customized for this application, is used in order to accomplish this aim under real time constraints. Different experimental results with a convoy of Pioneer P3-DX units tracking non-linear trajectories are shown. The paper shows that a simple setup based on low cost laser range systems and robot built-in odometry sensors is able to give a high degree of robustness and accuracy to the relative localization problem of convoy units for indoor applications.

Fuzzy Decentralized Control for guidance of a convoy of robots in non-linear trajectories

This article presents a control solution for the guidance of wheeled convoy units in non-linear trajectories. The proposal consists of a Mamdani fuzzy controller to solve the Decentralized Control problem as applied to a set of units following a leader, whilst guaranteeing the so called “string stability” condition of the convoy.

Adaptive Self-triggered Control of a Remotely Operated Robot

We consider the problem of remotely operating an autonomous robot through a wireless communication channel. Our goal is to achieve a satisfactory tracking performance while reducing network usage. To attain this objective we implement a self-triggered strategy that adjusts the triggering condition to the observed tracking error. After the theoretical justification we present experimental results from the application of this adaptive self-triggered approach on a P3-DX mobile robot remotely controlled. The experiments show a relevant reduction on the generated network traffic compared to a periodic implementation and to a non-adaptive self-triggered approach, while the tracking performance is barely degraded.

Adaptive self-triggered control of a remotely operated P3-DX robot

In this paper the problem of remotely operating an autonomous robot through a wireless communication channel is considered. The main goal is to achieve a satisfactory tracking performance while reducing network usage. To attain this objective, a self-triggered strategy that adjusts the triggering condition to the observed tracking error is implemented. After the theoretical justification, simulation results of a P3-DX mobile robot remotely controlled using TrueTime are presented. Also, the same adaptive self-triggered approach has been tested on a real robot. The experiments reinforce the relevant reduction on the generated network traffic compared to a periodic implementation and to a non-adaptive self-triggered approach, while the tracking performance is barely degraded. Remotely operated P3-DX robot through a wireless communication channel.Improving the NCS of a robotic unit by means of adaptive self-triggered control.Relevant network traffic decrease with negligible tracking performance reduction.A periodic control strategy validated by simulation and by real robotic demonstrator.

Event-Based Sensing and Control for Remote Robot Guidance: An Experimental Case

This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient use of communications and reduce sensor activity. Measurement requests are dictated by an event-based state estimator by setting an upper bound to the estimation error covariance matrix. The rest of the time, state prediction is carried out with the Unscented transformation. This prediction method makes it possible to select the appropriate instants at which to perform actuations on the robot so that guidance performance does not degrade below a certain threshold. Ultimately, we obtained a combined event-based control and estimation solution that drastically reduces communication accesses. The magnitude of this reduction is set according to the tracking error margin of a P3-DX robot following a nonlinear trajectory, remotely controlled with a mini PC and whose pose is detected by a camera sensor.

On-Board Event-Based State Estimation for Trajectory Approaching and Tracking of a Vehicle

For the problem of pose estimation of an autonomous vehicle using networked external sensors, the processing capacity and battery consumption of these sensors, as well as the communication channel load should be optimized. Here, we report an event-based state estimator (EBSE) consisting of an unscented Kalman filter that uses a triggering mechanism based on the estimation error covariance matrix to request measurements from the external sensors. This EBSE generates the events of the estimator module on-board the vehicle and, thus, allows the sensors to remain in stand-by mode until an event is generated. The proposed algorithm requests a measurement every time the estimation distance root mean squared error (DRMS) value, obtained from the estimators covariance matrix, exceeds a threshold value. This triggering threshold can be adapted to the vehicles working conditions rendering the estimator even more efficient. An example of the use of the proposed EBSE is given, where the autonomous vehicle must approach and follow a reference trajectory. By making the threshold a function of the distance to the reference location, the estimator can halve the use of the sensors with a negligible deterioration in the performance of the approaching maneuver.

Aperiodic linear networked control considering variable channel delays: application to robots coordination.

One of the main challenges in wireless cyber-physical systems is to reduce the load of the communication channel while preserving the control performance. In this way, communication resources are liberated for other applications sharing the channel bandwidth. The main contribution of this work is the design of a remote control solution based on an aperiodic and adaptive triggering mechanism considering the current network delay of multiple robotics units. Working with the actual network delay instead of the maximum one leads to abandoning this conservative assumption, since the triggering condition is fixed depending on the current state of the network. This way, the controller manages the usage of the wireless channel in order to reduce the channel delay and to improve the availability of the communication resources. The communication standard under study is the widespread IEEE 802.11g, whose channel delay is clearly uncertain. First, the adaptive self-triggered control is validated through the TrueTime simulation tool configured for the mentioned WiFi standard. Implementation results applying the aperiodic linear control laws on four P3-DX robots are also included. Both of them demonstrate the advantage of this solution in terms of network accessing and control performance with respect to periodic and non-adaptive self-triggered alternatives.

Implementation of robot routing approaches for convoy merging manoeuvres

Autonomous and cooperative guidance strategies for a convoy of electric vehicles in an urban context are challenging research topics in robotics and intelligent transportation systems. The vehicles that form the convoy eventually will have to leave it to perform a mission and return to the convoy formation once the mission has been accomplished. Nevertheless, the merging manoeuvres amongst the convoy and the units returning to it (pursuing units) is a complex task that involves the determination of the best merging point and the route across the city to reach it. This paper tackles this routing problem of a robot located in a map that is trying to join a convoy of robots in constant movement along a peripheral trajectory. We have developed two search strategies able to determine the optimal merging point and the best route to reach it: on one hand we describe a basic solution able to solve the problem when the time spent by the robot traveling along every street of the map is considered to be known and constant. On the other hand, we extended this basic approach to provide a new search strategy that considers uncertainty in traveling times. This increases considerably the complexity of the problem and makes necessary the inclusion of a risk factor that must be considered when determining the best route and the merging point for the manoeuvre. We also put our search strategies into practice in both, simulated and real scenarios. On one hand we have simulated the behavior of a convoy leader and a transport unit which is trying to join in the convoy, using Player&Stage. On the other hand we have used real P3-DX robot units as prototypes of electrical vehicles in a transport scenario.

Computation reduction of smart sensors for EBSE using Mahalanobis sampling

Event-based sampling strategies allow for reducing the amount of communications between a sensor and the estimation module. This reduction is interesting specially when the sensors are linked by a shared wireless network. This paper proposes new event-based sampling methods based on the Mahalanobis distance concept. Combined with an Event-Based State Estimator, they provide the same level of performance than other advanced sampling methods but keeping the computation simple enough to be executed by a smart sensor. The mentioned improvements of the algorithm respect other proposals are validated in simulation.