Visual-Based SLAM Configurations for Cooperative Multi-UAV Systems with a Lead Agent: An Observability-Based Approach

Juan-Carlos Trujillo; Rodrigo Munguia; Edmundo Guerra; Antoni Grau

doi:10.3390/s18124243

Visual-Based SLAM Configurations for Cooperative Multi-UAV Systems with a Lead Agent: An Observability-Based Approach

Sensors ◽

10.3390/s18124243 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4243 ◽

Cited By ~ 4

Author(s):

Juan-Carlos Trujillo ◽

Rodrigo Munguia ◽

Edmundo Guerra ◽

Antoni Grau

Keyword(s):

Fundamental Problem ◽

Position Estimation ◽

Level Control ◽

Aerial Robots ◽

Control Scheme ◽

High Level ◽

System Configurations ◽

Theoretical Results ◽

Multi Uav ◽

Nonlinear Observability

In this work, the problem of the cooperative visual-based SLAM for the class of multi-UA systems that integrates a lead agent has been addressed. In these kinds of systems, a team of aerial robots flying in formation must follow a dynamic lead agent, which can be another aerial robot, vehicle or even a human. A fundamental problem that must be addressed for these kinds of systems has to do with the estimation of the states of the aerial robots as well as the state of the lead agent. In this work, the use of a cooperative visual-based SLAM approach is studied in order to solve the above problem. In this case, three different system configurations are proposed and investigated by means of an intensive nonlinear observability analysis. In addition, a high-level control scheme is proposed that allows to control the formation of the UAVs with respect to the lead agent. In this work, several theoretical results are obtained, together with an extensive set of computer simulations which are presented in order to numerically validate the proposal and to show that it can perform well under different circumstances (e.g., GPS-challenging environments). That is, the proposed method is able to operate robustly under many conditions providing a good position estimation of the aerial vehicles and the lead agent as well.

Download Full-text

A Unified Approach for Multi-Point Cartesian Compliance Control of Serial Manipulators

Volume 2: 34th Annual Mechanisms and Robotics Conference, Parts A and B ◽

10.1115/detc2010-28094 ◽

2010 ◽

Author(s):

Phongsaen Pitakwatchara

Keyword(s):

Generalized Inverse ◽

Impedance Control ◽

Level Control ◽

Unified Approach ◽

Relative Priority ◽

Multiple Points ◽

Serial Manipulators ◽

Control Scheme ◽

Planning Algorithm ◽

High Level

This paper proposes a unified approach for controlling the Cartesian compliance of multiple points assigned along the linkage chains of the manipulator. The method applies two key frameworks. Task-priority based control is used to synergistically plan the tasks of the advanced manipulation according to their relative priority. Then, the impedance control scheme is employed for implementing the controller. Additionally, with the use of generalized inverse theory throughout the development, the method is capable of controlling the manipulator at the singularities seamlessly. This low-level control system may be integrated with the high-level manipulation planning algorithm, which generates the online dynamical tasks based on the desired behavior and the sensor information, to accomplish the demanding operation.

Download Full-text

A Model of Caterpillar Locomotion Based on Assur Tensegrity Structures

Volume 6: 35th Mechanisms and Robotics Conference, Parts A and B ◽

10.1115/detc2011-47708 ◽

2011 ◽

Cited By ~ 7

Author(s):

Omer Orki ◽

Offer Shai ◽

Amir Ayali ◽

Uri Ben-Hanan

Keyword(s):

Hydrostatic Pressure ◽

Control Algorithm ◽

Control Unit ◽

Engineering Properties ◽

Level Control ◽

Tensegrity Structures ◽

Control Scheme ◽

High Level ◽

Longitudinal Muscles ◽

Ongoing Project

This paper presents an ongoing project aiming at building a robot composed of Assur tensegrity structures, which mimics caterpillar locomotion. Caterpillars are soft-bodied animals capable of making complex movements with astonishing fault-tolerance. In our model, each caterpillar segment is represented by a 2D tensegrity triad consisting of two bars connected by two cables and a strut. The cables represent the major longitudinal muscles of the caterpillar, while the strut represents hydrostatic pressure. The control scheme in this model is divided into localized low-level controllers and a high-level control unit. The unique engineering properties of Assur tensegrity structures, which were mathematically proved last year, together with the suggested control algorithm provide the model with robotic softness. Moreover, the degree of softness can be continuously changed during simulation, making this model suitable for simulation of soft-bodied caterpillars as well as other types of soft animals.

Download Full-text

Multi-Objective Supervisory Control for DC/DC Converters in Advanced Aeronautic Applications

Energies ◽

10.3390/en11113216 ◽

2018 ◽

Vol 11 (11) ◽

pp. 3216 ◽

Cited By ~ 5

Author(s):

Alberto Cavallo ◽

Giacomo Canciello ◽

Beniamino Guida ◽

Ponggorn Kulsangcharoen ◽

Seang Yeoh ◽

...

Keyword(s):

Low Voltage ◽

Control Strategies ◽

Gain Control ◽

High Gain ◽

Level Control ◽

Mathematical Arguments ◽

Control Scheme ◽

Sliding Manifold ◽

High Gain Control ◽

High Level

In this paper, an intelligent control strategy for DC/DC converters is proposed. The converter connects two DC busses, a high-voltage and a low-voltage bus. The control scheme is composed by a two-layer architecture, a low-level control based on the concept of sliding manifold, and high gain control, and a high-level control used to guarantee the achievement of various objectives. The proposed control strategies are based on solid mathematical arguments, with stability proofs for the non-linear case, and decision trees for parameter selection. The paper results are analyzed and discussed by using simulation at different detail levels in MATLAB/Stateflow/PowerSystem, and validated by experimental results, also considering MIL standard performance indices.

Download Full-text

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

Remote Sensing ◽

10.3390/rs13173419 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3419

Author(s):

Francisco Bonnin-Pascual ◽

Emilio Garcia-Fidalgo ◽

Joan P. Company-Corcoles ◽

Alberto Ortiz

Keyword(s):

Visual Inspection ◽

Obstacle Detection ◽

Level Control ◽

Control Software ◽

Full System ◽

Aerial Robots ◽

Collision Prevention ◽

Cost Efficient ◽

Inspection Tasks ◽

High Level

Because of their high maneuverability and fast deployment times, aerial robots have recently gained popularity for automating inspection tasks. In this paper, we address the visual inspection of vessel cargo holds, aiming at safer, cost-efficient and more intensive visual inspections of ships by means of a multirotor-type platform. To this end, the vehicle is equipped with a sensor suite able to supply the surveyor with imagery from relevant areas, while the control software is supporting the operator during flight with enhanced functionalities and reliable autonomy. All this has been accomplished in the context of the supervised autonomy (SA) paradigm, by means of extensive use of behaviour-based high-level control (including obstacle detection and collision prevention), all specifically devised for visual inspection. The full system has been evaluated both in laboratory and in real environments, on-board two different vessels. Results show the vehicle effective for the referred application, in particular due to the inspection-oriented capabilities it has been fitted with.

Download Full-text

Finite-Time Adaptive Fuzzy Control for Nonlinear Systems with Unknown Backlash-Like Hysteresis

International Journal of Fuzzy Systems ◽

10.1007/s40815-021-01066-1 ◽

2021 ◽

Author(s):

Shuzhen Diao ◽

Wei Sun ◽

Le Wang ◽

Jing Wu

Keyword(s):

Fuzzy Control ◽

Finite Time ◽

Fuzzy Systems ◽

Tracking Error ◽

Adaptive Fuzzy Control ◽

Finite Time Stability ◽

Adaptive Fuzzy ◽

Intermediate Variable ◽

Control Scheme ◽

Theoretical Results

AbstractThis study considers the tracking control problem of the nonstrict-feedback nonlinear system with unknown backlash-like hysteresis, and a finite-time adaptive fuzzy control scheme is developed to address this problem. More precisely, the fuzzy systems are employed to approximate the unknown nonlinearities, and the design difficulties caused by the nonlower triangular structure are also overcome by using the property of fuzzy systems. Besides, the effect of unknown hysteresis input is compensated by approximating an intermediate variable. With the aid of finite-time stability theory, the proposed control algorithm could guarantee that the tracking error converges to a smaller region. Finally, a simulation example is provided to further verify the above theoretical results.

Download Full-text

Multi-Sensor Fusion for Aerial Robots in Industrial GNSS-Denied Environments

Applied Sciences ◽

10.3390/app11093921 ◽

2021 ◽

Vol 11 (9) ◽

pp. 3921

Author(s):

Paloma Carrasco ◽

Francisco Cuesta ◽

Rafael Caballero ◽

Francisco J. Perez-Grau ◽

Antidio Viguria

Keyword(s):

Sensor Fusion ◽

Computational Efficiency ◽

Probabilistic Approach ◽

Laser Scanner ◽

Industrial Applications ◽

Experimental Results ◽

Added Value ◽

Aerial Robots ◽

3D Localization ◽

High Level

The use of unmanned aerial robots has increased exponentially in recent years, and the relevance of industrial applications in environments with degraded satellite signals is rising. This article presents a solution for the 3D localization of aerial robots in such environments. In order to truly use these versatile platforms for added-value cases in these scenarios, a high level of reliability is required. Hence, the proposed solution is based on a probabilistic approach that makes use of a 3D laser scanner, radio sensors, a previously built map of the environment and input odometry, to obtain pose estimations that are computed onboard the aerial platform. Experimental results show the feasibility of the approach in terms of accuracy, robustness and computational efficiency.

Download Full-text

Wildlife Monitoring Using a Multi-UAV System with Optimal Transport Theory

Applied Sciences ◽

10.3390/app11094070 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4070

Author(s):

Rabiul Hasan Kabir ◽

Kooktae Lee

Keyword(s):

Detection Rate ◽

Transport Theory ◽

Optimal Transport ◽

Position Estimation ◽

Wildlife Monitoring ◽

High Detection Rate ◽

Monitoring Strategies ◽

Spatio Temporal ◽

Optimal Transport Theory ◽

Multi Uav

This paper addresses a wildlife monitoring problem using a team of unmanned aerial vehicles (UAVs) with the optimal transport theory. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based sensing or GPS trackers. However, there still exist unsolved problems as to how the UAVs need to cover a spacious domain to detect animals as many as possible. In this paper, we propose the optimal transport-based wildlife monitoring strategy for a multi-UAV system, to prioritize monitoring areas while incorporating complementary information such as GPS trackers and satellite-based sensing. Through the proposed scheme, the UAVs can explore the large-size domain effectively and collaboratively with a given priority. The time-varying nature of wildlife due to their movements is modeled as a stochastic process, which is included in the proposed work to reflect the spatio-temporal evolution of their position estimation. In this way, the proposed monitoring plan can lead to wildlife monitoring with a high detection rate. Various simulation results including statistical data are provided to validate the proposed work. In all different simulations, it is shown that the proposed scheme significantly outperforms other UAV-based wildlife monitoring strategies in terms of the target detection rate up to 3.6 times.

Download Full-text

Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽

10.3390/s21072534 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2534

Author(s):

Oualid Doukhi ◽

Deok-Jin Lee

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Autonomous Navigation ◽

Control Technique ◽

Local Motion ◽

Aerial Robots ◽

Novel Approach ◽

Outdoor Environments ◽

Aerial Vehicle ◽

High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

Download Full-text