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See detailA Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles
Castillo Lopez, Manuel UL; Ludivig, Philippe; Sajadi-Alamdari, Seyed Amin et al

in IEEE Robotics and Automation Letters (RA-L) (2020)

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies ... [more ▼]

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an obstacle's space: a polyhedron, such as a cuboid, or a nonlinear differentiable surface, such as an ellipsoid. The former approach relies on disjunctive programming, which has a relatively high computational cost that grows exponentially with the number of obstacles. The latter approach needs to be linearized locally to find a tractable evaluation of the chance constraints, which dramatically reduces the remaining free space and leads to over-conservative trajectories or even unfeasibility. In this work, we present a hybrid approach that eludes the pitfalls of both strategies while maintaining the original safety guarantees. The key idea consists in obtaining a safe differentiable approximation for the disjunctive chance constraints bounding the obstacles. The resulting nonlinear optimization problem is free of chance constraint linearization and disjunctive programming, and therefore, it can be efficiently solved to meet fast real-time requirements with multiple obstacles. We validate our approach through mathematical proof, simulation and real experiments with an aerial robot using nonlinear model predictive control to avoid pedestrians. [less ▲]

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See detailA case study on the impact of masking moving objects on the camera pose regression with CNNs
Cimarelli, Claudio UL; Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL et al

in 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2019, November 25)

Robot self-localization is essential for operating autonomously in open environments. When cameras are the main source of information for retrieving the pose, numerous challenges are posed by the presence ... [more ▼]

Robot self-localization is essential for operating autonomously in open environments. When cameras are the main source of information for retrieving the pose, numerous challenges are posed by the presence of dynamic objects, due to occlusion and continuous changes in the appearance. Recent research on global localization methods focused on using a single (or multiple) Convolutional Neural Network (CNN) to estimate the 6 Degrees of Freedom (6-DoF) pose directly from a monocular camera image. In contrast with the classical approaches using engineered feature detector, CNNs are usually more robust to environmental changes in light and to occlusions in outdoor scenarios. This paper contains an attempt to empirically demonstrate the ability of CNNs to ignore dynamic elements, such as pedestrians or cars, through learning. For this purpose, we pre-process a dataset for pose localization with an object segmentation network, masking potentially moving objects. Hence, we compare the pose regression CNN trained and/or tested on the set of masked images and the original one. Experimental results show that the performances of the two training approaches are similar, with a slight reduction of the error when hiding occluding objects from the views. [less ▲]

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See detailFaster Visual-Based Localization with Mobile-PoseNet
Cimarelli, Claudio UL; Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL et al

in International Conference on Computer Analysis of Images and Patterns (2019, August 22)

Precise and robust localization is of fundamental importance for robots required to carry out autonomous tasks. Above all, in the case of Unmanned Aerial Vehicles (UAVs), efficiency and reliability are ... [more ▼]

Precise and robust localization is of fundamental importance for robots required to carry out autonomous tasks. Above all, in the case of Unmanned Aerial Vehicles (UAVs), efficiency and reliability are critical aspects in developing solutions for localization due to the limited computational capabilities, payload and power constraints. In this work, we leverage novel research in efficient deep neural architectures for the problem of 6 Degrees of Freedom (6-DoF) pose estimation from single RGB camera images. In particular, we introduce an efficient neural network to jointly regress the position and orientation of the camera with respect to the navigation environment. Experimental results show that the proposed network is capable of retaining similar results with respect to the most popular state of the art methods while being smaller and with lower latency, which are fundamental aspects for real-time robotics applications. [less ▲]

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See detailDeep Reinforcement Learning based Continuous Control for Multicopter Systems
Manukyan, Anush UL; Olivares Mendez, Miguel Angel UL; Geist, Matthieu et al

in International Conference on Control, Decision and Information CoDIT, Paris 23-26 April 2019 (2019, April 26)

In this paper we apply deep reinforcement learning techniques on a multicopter for learning a stable hovering task in a continuous action state environment. We present a framework based on OpenAI GYM ... [more ▼]

In this paper we apply deep reinforcement learning techniques on a multicopter for learning a stable hovering task in a continuous action state environment. We present a framework based on OpenAI GYM, Gazebo and RotorS MAV simulator, utilized for successfully training different agents to perform various tasks. The deep reinforcement learning method used for the training is model-free, on-policy, actor-critic based algorithm called Trust Region Policy Optimization (TRPO). Two neural networks have been used as a nonlinear function approximators. Our experiments showed that such learning approach achieves successful results, and facilitates the process of controller design. [less ▲]

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See detailVision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers
Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL; Sanchez Lopez, Jose Luis UL et al

in IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society (2019)

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See detailReal-Time Human Head Imitation for Humanoid Robots
Cazzato, Dario UL; Cimarelli, Claudio UL; Sanchez Lopez, Jose Luis UL et al

in Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality (2019)

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See detailTowards trajectory planning from a given path for multirotor aerial robots trajectory tracking
Sanchez Lopez, Jose Luis UL; Olivares Mendez, Miguel Angel UL; Castillo Lopez, Manuel UL et al

in 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas 12-15 June 2018 (2018, June)

Planning feasible trajectories given desired collision-free paths is an essential capability of multirotor aerial robots that enables the trajectory tracking task, in contrast to path following. This ... [more ▼]

Planning feasible trajectories given desired collision-free paths is an essential capability of multirotor aerial robots that enables the trajectory tracking task, in contrast to path following. This paper presents a trajectory planner for multirotor aerial robots carefully designed considering the requirements of real applications such as aerial inspection or package delivery, unlike other research works that focus on aggressive maneuvering. Our planned trajectory is formed by a set of polynomials of two kinds, acceleration/deceleration and constant velocity. The trajectory planning is carried out by means of an optimization that minimizes the trajectory tracking time, applying some typical constraints as m-continuity or limits on velocity, acceleration and jerk, but also the maximum distance between the trajectory and the given path. Our trajectory planner has been tested in real flights with a big and heavy aerial platform such the one that would be used in a real operation. Our experiments demonstrate that the proposed trajectory planner is suitable for real applications and it is positively influencing the controller for the trajectory tracking task. [less ▲]

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See detailModel Predictive Control for Aerial Collision Avoidance in Dynamic Environments
Castillo Lopez, Manuel UL; Sajadi Alamdari, Seyed Amin UL; Sanchez Lopez, Jose Luis UL et al

in 26th Mediterranean Conference on Control and Automation (MED), Zadar, Croatia, 19-22 June 2018 (2018, June)

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic ... [more ▼]

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). A new nonlinear model predictive control (NMPC) approach is proposed to safely navigate in a workspace populated by static and/or moving obstacles. The uniqueness of our approach lies in its ability to anticipate the dynamics of multiple obstacles, avoiding them in real-time. Exploiting active set algorithms, only the obstacles that affect to the UAV during the prediction horizon are considered at each sample time. We also improve the fluency of avoidance maneuvers by reformulating the obstacles as orientable ellipsoids, being less prone to local minima and allowing the definition of a preferred avoidance direction. Finally, we present two real-time implementations based on simulation. The former demonstrates that our approach outperforms its analog static formulation in terms of safety and efficiency. The latter shows its capability to avoid multiple dynamic obstacles. [less ▲]

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See detailCollision Avoidance Effects on the Mobility of a UAV Swarm Using Chaotic Ant Colony with Model Predictive Control
Dentler, Jan Eric UL; Rosalie, Martin UL; Danoy, Grégoire UL et al

in Journal of Intelligent \& Robotic Systems (2018)

The recent development of compact and economic small Unmanned Aerial Vehicles (UAVs) permits the development of new UAV swarm applications. In order to enhance the area coverage of such UAV swarms, a ... [more ▼]

The recent development of compact and economic small Unmanned Aerial Vehicles (UAVs) permits the development of new UAV swarm applications. In order to enhance the area coverage of such UAV swarms, a novel mobility model has been presented in previous work, combining an Ant Colony algorithm with chaotic dynamics (CACOC). This work is extending CACOC by a Collision Avoidance (CA) mechanism and testing its efficiency in terms of area coverage by the UAV swarm. For this purpose, CACOC is used to compute UAV target waypoints which are tracked by model predictively controlled UAVs. The UAVs are represented by realistic motion models within the virtual robot experimentation platform (V-Rep). This environment is used to evaluate the performance of the proposed CACOC with CA algorithm in an area exploration scenario with 3 UAVs. Finally, its performance is analyzed using metrics. [less ▲]

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See detailA Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments
Sanchez Lopez, Jose Luis UL; Wang, Min UL; Olivares Mendez, Miguel Angel UL et al

in Journal of Intelligent and Robotic Systems (2018)

Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for ... [more ▼]

Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for multirotor aerial robots to obtain a feasible, optimal and collision-free path in complex dynamic environments. High-level geometric primitives are employed to compactly represent the situation, which includes self-situation of the robot and situation of the obstacles in the environment. A probabilistic graph is utilized to sample the admissible space without taking into account the existing obstacles. Whenever a planning query is received, the generated probabilistic graph is then explored by an A$^{\star}$ discrete search algorithm with an artificial field map as cost function in order to obtain a raw optimal collision-free path, which is subsequently shortened. Realistic simulations in V-REP simulator have been created to validate the proposed path planning solution, integrating it into a fully autonomous multirotor aerial robotic system. [less ▲]

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See detailAnalyzing and improving multi-robot missions by using process mining
Roldán, Juan Jesús; Olivares Mendez, Miguel Angel UL; del Cerro, Jaime et al

in Autonomous Robots (2017)

Multi-robot missions can be compared to industrial processes or public services in terms of complexity, agents and interactions. Process mining is an emerging discipline that involves process modeling ... [more ▼]

Multi-robot missions can be compared to industrial processes or public services in terms of complexity, agents and interactions. Process mining is an emerging discipline that involves process modeling, analysis and improvement through the information collected by event logs. Currently, this discipline is successfully used to analyze several types of processes, but is hardly applied in the context of robotics. This work proposes a systematic protocol for the application of process mining to analyze and improve multi-robot missions. As an example, this protocol is applied to a scenario of fire surveillance and extinguishing with a fleet of UAVs. The results show the potential of process mining in the analysis of multi-robot missions and the detection of problems such as bottlenecks and inefficiencies. This work opens the way to an extensive use of these techniques in multi-robot missions, allowing the development of future systems for optimizing missions, allocating tasks to robots, detecting anomalies or supporting operator decisions. [less ▲]

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See detailEvasive Maneuvering for UAVs: An MPC Approach
Castillo Lopez, Manuel UL; Olivares Mendez, Miguel Angel UL; Voos, Holger UL

in ROBOT'2017 - Third Iberian Robotics Conference, Sevilla, Spain, 2017 (2017, November 22)

Flying autonomously in a workspace populated by obstacles is one of the main goals when working with Unmanned Aerial Vehicles (UAV). To address this challenge, this paper presents a model predictive ... [more ▼]

Flying autonomously in a workspace populated by obstacles is one of the main goals when working with Unmanned Aerial Vehicles (UAV). To address this challenge, this paper presents a model predictive flight controller that drives the UAV through collision-free trajectories to reach a given pose or follow a way-point path. The major advantage of this approach lies on the inclusion of three-dimensional obstacle avoidance in the control layer by adding ellipsoidal constraints to the optimal control problem. The obstacles can be added, moved and resized online, providing a way to perform waypoint navigation without the need of motion planning. In addition, the delays of the system are considered in the prediction by an experimental first order with delay model of the system. Successful experiments in 3D path tracking and obstacle avoidance validates its effectiveness for sense-and-avoid and surveillance applications presenting the proper structure to extent its autonomy and applications. [less ▲]

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See detailA Perspective of Security for Mobile Service Robots
Cornelius, Gary Philippe UL; Hochgeschwender, Nico UL; Voos, Holger UL et al

in Iberian Robotics Conference, Seville, Spain, 2017 (2017, November 22)

Future homes will contain Mobile Service Robots (MSR) with diverse functionality. MSRs act in close proximity to humans and have the physical capabilities to cause serious harm to their environment ... [more ▼]

Future homes will contain Mobile Service Robots (MSR) with diverse functionality. MSRs act in close proximity to humans and have the physical capabilities to cause serious harm to their environment. Furthermore, they have sensors that gather large amounts of data, which might contain sensitive information. A mobile service robot’s physical capabilities are controlled by networked computers susceptible to faults and intrusions. The proximity to humans and the possibility to physically interact with them makes it critical to think about the security issues of MSRs. In this work, we investigate possible attacks on mobile service robots. We survey adversary motivations to attack MSRs, analyse threat vectors and list different available defence mechanisms against attacks on MSRs. [less ▲]

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See detailImplementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in 2017 IEEE Conference on Control Technology and Applications (CCTA) (2017, August 30)

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined ... [more ▼]

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) [1] as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs). The source code of the proposed framework is available under [2]. [less ▲]

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See detailOperational space control of a lightweight robotic arm actuated by shape memory alloy wires: A comparative study
Quintanar Guzman, Serket UL; Kannan, Somasundar UL; Aguilera Gonzalez, Adriana UL et al

in Journal of Intelligent Material Systems & Structures (2017)

This article presents the design and control of a two-link lightweight robotic arm using shape memory alloy wires as actuators. Both a single-wire actuated system and an antagonistic configuration system ... [more ▼]

This article presents the design and control of a two-link lightweight robotic arm using shape memory alloy wires as actuators. Both a single-wire actuated system and an antagonistic configuration system are tested in open and closed loops. The mathematical model of the shape memory alloy wire, as well as the kinematics and dynamics of the robotic arm, are presented. The operational space control of the robotic arm is performed using a joint space control in the inner loop and closed-loop inverse kinematics in the outer loop. In order to choose the best joint space control approach, a comparative study of four different control approaches (proportional derivative, sliding mode, adaptive, and adaptive sliding mode control) is carried out for the proposed model. From this comparative analysis, the adaptive controller was chosen to perform operational space control. This control helps us to perform accurate positioning of the end-effector of shape memory alloy wire–based robotic arm. The complete operational space control was successfully tested through simulation studies performing position reference tracking in the end-effector space. Through simulation studies, the proposed control solution is successfully verified to control the hysteretic robotic arm. [less ▲]

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See detailArea exploration with a swarm of UAVs combining deterministic Chaotic Ant Colony Mobility with position MPC
Rosalie, Martin UL; Dentler, Jan Eric UL; Danoy, Grégoire UL et al

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, July 27)

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already ... [more ▼]

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already proposed a new mobility model using Ant Colony Algorithms combined with chaotic dynamics (CACOC) to enhance the coverage of an area by a swarm of UAVs. In this paper we propose to consider this mobility model as waypoints for real UAVs. A control model of the UAVs is deployed to test the efficiency of the coverage of an area by the swarm. We have tested our approach in a realistic robotics simulator (V-Rep) which is connected with ROS. We compare the performance in terms of coverage using several metrics to ensure that this mobility model is efficient for real UAVs. [less ▲]

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See detailMulti-Robot Interfaces and Operator Situational Awareness: Study of the Impact of Immersion and Prediction
Roldán, Juan Jesús; Peña-Tapia, Elena; Martín-Barrio, Andrés et al

in Sensors (2017), 17(8 1720),

Multi-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation ... [more ▼]

Multi-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation properly, make decisions, generate the adequate commands, and send them to the robots. The consequences of excessive workload and lack of awareness can vary from inefficiencies to accidents. This work focuses on the study of future operator interfaces of multi-robot systems, taking into account relevant issues such as multimodal interactions, immersive devices, predictive capabilities and adaptive displays. Specifically, four interfaces have been designed and developed: a conventional, a predictive conventional, a virtual reality and a predictive virtual reality interface. The four interfaces have been validated by the performance of twenty-four operators that supervised eight multi-robot missions of fire surveillance and extinguishing. The results of the workload and situational awareness tests show that virtual reality improves the situational awareness without increasing the workload of operators, whereas the effects of predictive components are not significant and depend on their implementation. [less ▲]

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See detailReal time degradation identification of UAV using machine learning techniques
Manukyan, Anush UL; Olivares Mendez, Miguel Angel UL; Geist, Matthieu et al

in International Conference on Unmanned Aircraft Systems ICUAS. Miami, USA, 2017 (2017, June 13)

The usages and functionalities of Unmanned Aerial Vehicles (UAV) have grown rapidly during the last years. They are being engaged in many types of missions, ranging from military to agriculture passing by ... [more ▼]

The usages and functionalities of Unmanned Aerial Vehicles (UAV) have grown rapidly during the last years. They are being engaged in many types of missions, ranging from military to agriculture passing by entertainment and rescue or even delivery. Nonetheless, for being able to perform such tasks, UAVs have to navigate safely in an often dynamic and partly unknown environment. This brings many challenges to overcome, some of which can lead to damages or degradations of different body parts. Thus, new tools and methods are required to allow the successful analysis and identification of the different threats that UAVs have to manage during their missions or flights. Various approaches, addressing this domain, have been proposed. However, most of them typically identify the changes in the UAVs behavior rather than the issue. This work presents an approach, which focuses not only on identifying degradations of UAVs during flights, but estimate the source of the failure as well. [less ▲]

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See detailModel predictive control for cooperative control of space robots
Kannan, Somasundar UL; Sajadi Alamdari, Seyed Amin UL; Dentler, Jan Eric UL et al

in Model predictive control for cooperative control of space robots (2017, January)

The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through ... [more ▼]

The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through manipulators are discussed. The Model Predictive Control (MPC) technique is briefly presented and successfully tested through simulations on two cases of position control of passive body in the orbit. [less ▲]

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See detailReal-time graph-based SLAM in unknown environments using a small UAV
Annaiyan, Arun UL; Olivares Mendez, Miguel Angel UL; Voos, Holger UL

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS); Miami 13-16 June 2017 (2017)

Autonomous navigation of small Unmanned Aerial Vehicles (UAVs) in cluttered environments is still a challenging problem. In this work, we present an approach based on graph slam and loop closure detection ... [more ▼]

Autonomous navigation of small Unmanned Aerial Vehicles (UAVs) in cluttered environments is still a challenging problem. In this work, we present an approach based on graph slam and loop closure detection for online mapping of unknown outdoor environments using a small UAV. Here, we used an onboard front facing stereo camera as the primary sensor. The data extracted by the cameras are used by the graph-based slam algorithm to estimate the position and create the graph-nodes and construct the map. To avoid multiple detections of one object as different objects and to identify re-visited locations, a loop closure detection is applied with optimization algorithm using the g2o toolbox to minimize the error. Furthermore, 3D occupancy map is used to represent the environment. This technique is used to save memory and computational time for the online processing. Real experiments are conducted in outdoor cluttered and open field environments.The experiment results show that our presented approach works under real time constraints, with an average time to process the nodes of the 3D map is 17.79ms. [less ▲]

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