Accuracy and safety are necessary characteristics in social navigation. These characteristics still constitute a challenge in this area. Yet, human comfort is the main goal in interactions involving human beings. The ROS Navigation Stack (RNS) allows the variation of local path planning methods. This paper consists in a comparative study of methods related to social navigation. This study promotes

This paper focuses on a 4-mecanum wheeled mobile robot used for transportation tasks in manufacturing industry. It aims to supervise the health state of the robot actuators after a first detection of faults, and to study the faults impact on the robot behavior. As faults are considered the loss of actuators efficiency due to wear linked to the robot high solicitation. The main contribution is on the

Autonomous vehicles require high-level semantic maps, which contain the activities of pedestrians and cars, to ensure safe navigation. High-level semantics can be obtained from mobile probe sensor data. Analyzing pedestrian trajectories obtained from mobile probe data is an effective approach to avoid collisions between autonomous vehicles and pedestrians. Such analyses of pedestrian trajectories can

In this paper, an adaptive motion-force control scheme is presented for a networked ultrasound robotic manipulator to perform a transversal abdomen scan. An adaptive backstepping position controller is designed to ensure the stability of the ultrasound robot in the presence of parametric uncertainties and external disturbances. A proportional-integral-derivative force controller is proposed to maintain

Engineering swarms of cyber-physical systems (CPSs) is a complex process. We present the CPSwarm workbench that creates an automated design workflow to ease this process. This formalized workflow guides the user from modeling, to code generation, to deployment, both in simulation and on CPS hardware platforms. The workbench combines existing and emerging tools to solve real-world CPS swarm problems

This paper reviews the existing vision-based tactile sensor (VBTS) designs reported in the literature. Although some reviews on VBTSs already exist in the literature. We believe it is necessary to review existing VBTS designs to formulate a guideline for developing such systems considering recent developments in the manufacturing and imaging technologies. Therefore, the main emphasis of this paper

This paper proposes a new control method for the ground moving target tracking problem by a fixed-wing unmanned aerial vehicle (UAV) with a monocular pan-tilt camera. By utilizing the image-based visual servoing, the control law can be directly designed in the image plane, thereby avoiding errors caused by the 3D position calculation. Based on that, we design a control framework to integrate the control

Learning-based visual localization has become prospective over the past decades. Since ground truth pose labels are difficult to obtain, recent methods try to learn pose estimation networks using pixel-perfect synthetic data. However, this also introduces the problem of domain bias. In this paper, we first build a Tuebingen Buildings dataset of RGB images collected by a drone in urban scenes and create

This article concerns tracking of floating objects using fixed-wing UAVs with a monocular thermal camera. Target tracking from an agile aerial vehicle is challenging because uncertainty in the UAV pose negatively affects the accuracy of the measurements obtained through thermal images. Consequently, the accuracy of the tracking estimates is degraded if navigation uncertainty is neglected. This is especially

Gait disabilities empowered intensive research on the field of human-robot interaction to promote effective gait rehabilitation. Assist-as-needed strategies are becoming prominent, appealing to the users’ participation in their rehabilitation therapy. This study proposes and assesses the biomechanical effects of an adaptive impedance control strategy that innovatively allows adaptability in interaction-based

In many practical applications of robot path planning, finding the shortest path is critical, while the response time is often overlooked but important. To address the problems of search node divergence and long calculation time in the A* routing algorithm in the large scenario, this paper presents a novel center constraint weighted A* algorithm (CCWA*). The heuristic function is modified to give different

In this paper, we study the conventional and learning-based control approaches for multi-rotor platforms, with and without the presence of an actuated “tail” appendage. A comprehensive experimental comparison between the proven control-theoretic approaches and more recent learning-based ones is one of the contributions. Furthermore, an actuated tail appendage is considered as a deviation from the typical

As an effort of automating the bridge inspection process, this paper presents a new development of an adaptable tank-like robot, which can climb on steel structures to collect data and perform inspection. While most current steel climbing mobile robots are designed to work on flat steel surface, our proposed tank-like robot design is capable of climbing on different steel structural shapes (e.g., cylinder

In this study, a novel semi-absolute method of localization and subsequent odometry: Structure Aided Odometry (SAO) for precision navigation in low-feature large scale environments, is proposed and validated. Storage racks and ceiling corrugation patterns are used to calculate orientation, cross-track, and along-track estimates for a warehouse robot to produce odometry with minimal drift. A comparison

Aerial physical interaction is a promising field for unmanned aerial vehicles in future applications. This paper presents a novel paradigm for automatic aerial contact-based sliding interaction (inspection/cleaning) tasks in aerial robotics allowing a 3D force with a constant norm to be applied on generic surfaces with unknown geometry. The interaction task is achieved by a fully-actuated hexarotor

A method for robot control is proposed in this paper to suppress human-caused disturbance in human-robot collaborative manipulation. In the method, the robot control algorithms are chosen according to the impacts of human motion on the manipulated objects: the modified model predictive controller is used when the impact is large, and the impedance controller is used when the impact is small. In the

This paper investigates the use of Deep Reinforcement Learning (DRL) applied to the humanoid robot soccer environment, where a robot must learn from basic to complex skills while it interacts with the environment through images received by its own camera. To do so, the Dueling Double DQN algorithm is used: it receives the images from the robot’s camera and decides on which discrete action should be

This work proposes a novel approach for improving the control performance of Unmanned Aerial Vehicles (UAVs) through cooperative reinforcement learning. By sharing their experience, it is shown that multiple UAVs can work together to converge on a set of optimal Model Predictive Control (MPC) parameters faster than when working on their own. In order to benefit from this shared experience, the UAVs

Transformable Unmanned Aerial Systems (UASs) are increasingly attracting attention in recent years due to their maneuverability, agility and morphological capacities. They have overcame many limitations such as, multi-tasks problem, structural adaptation in flight, energy consumption, fault tolerant control, and maneuverability. Nevertheless, their variable geometries as well as the great number of

Ground reaction force (GRF) plays an integral role in legged robots to control interaction with the ground. However, most techniques in whole-body controller for quadrupedal robots do not explicitly take into account actual torque or force in their control loops and instead use feed-forward force to generate joint torque at every time step. In this paper, we present a closed-loop whole-body controller

This paper addresses the issue of cooperative control concerning the output synchronization of the linear time-invariant multi-input multi-output multi-agent system i.e., multi-unmanned aerial vehicle (a swarm of the drone), by designing observer-based consensus protocol with directed communication topology. Considering the leader following consensus tracking problem, an observer-based protocol is

This paper presents a novel light-weighted Unmanned Aerial Vehicle (UAV), an over-actuated tilt-rotor quadrotor with an innovative control allocation technique, named as Fast Control Allocation (FCA). In this arrangement, every motor has its own independent tilting command angle. By using this novel approach, the aircraft enhances its yawing capability and increases one more actuation domain: forward/backward

The unmanned robotic excavator system has recently become one solution for rescue at the disaster site. Almost all of the solutions about excavator automation have used the electric valve controller and pressure sensor through the mechanical modifications since they are essential. However, some problems might occur because of unpredictable cost and time consumption in modifying the hydraulic drive

In this paper (A preliminary version of the submitted paper appeared in the Proceedings of the 2020 International Conference on Unmanned Aircraft Systems (ICUAS’20), Athens, Greece*), a robust attitude controller is proposed for a small-scale helicopter based on Multi-Variable Super Twisting Algorithm. An interconnected hybrid model of a helicopter is considered consisting of fuselage and rotor which

A safe integration of UAVs into the airspace is fundamental to unblock all the potential of drone applications. U-space is the drone traffic management solution for Europe, intended to handle a large number of drones into the airspace, especially at Very Low Level (VLL). This paper is focused on conflict management for multiple unmanned aerial vehicles in the context of the U-space under 4D trajectory

This paper investigates a novel hybrid gait obstacle-avoidance control strategy based on a perception system for the six wheel-legged robot (BIT-6NAZA) in uneven terrain. This robot has stronger payload transportation performance benefited from the flexibility of the 6-degree of freedom Stewart platform. It can guarantee the attitude level stability when passing through different shapes of obstacles

The development of Human Robot Collaborative (HRC) systems faces many challenges. First, HRC systems should be adaptable and re-configurable to support fast production changes. However, in the development of HRC applications safety considerations are of paramount importance, as much as classical activities such as task programming and deployment. Hence, the reconfiguration and reprogramming of executing

Benchmarking is a common practice employed to quantify the performance of various approaches toward the same task. By maintaining a consistent test environment, the inherent behaviours between methods may be distinguished—which is key to progressing a research field. In robotic manipulation research there is a current lack of standardisation, making it challenging to fairly assess and compare various

This article tackles the challenge of negative pressure adhesion control of a Vortex Robotic (VR) platform, which utilizes a modified Electric Ducted Fan (EDF)-based design for successfully adhering to surfaces of variable curvature. The resulting Vortex Actuation (VA) system is estimated through a switching Autoregressive-Moving-Average with eXternal input (ARMAX) identification, for accurately capturing

This paper presents a complete topological navigation system for a resource-constrained mobile robot like Pepper, based on image memory and the teach-and-repeat paradigm. Image memory is constructed from a set of reference images that are acquired during a prior mapping phase and arranged topologically. A* search is used to find the optimal path between the current location and the destination. The

Visual scene recognition is an indispensable part of automatic localization and navigation. In the same scene, the appearance and viewpoint may be changed greatly, which is the largest challenge for some advanced unmanned systems,e.g. robot,vehicle and UAV,etc., to identify scenes where they have visited. Traditional methods have been subjected to hand-made feature-based paradigms for a long time,

This article contributes with a methodology based on deep reinforcement learning to develop running skills in a humanoid robot with no prior knowledge. Specifically, the algorithm used for learning is the Proximal Policy Optimization (PPO). The chosen application domain is the RoboCup 3D Soccer Simulation (Soccer 3D), a competition where teams composed by 11 autonomous agents each compete in simulated

Particle Filters (PFs) have been successfully employed for monocular 3D model-based tracking of rigid objects. However, these filters depend on the computation of importance weighs that use sub-optimal approximations to the likelihood function. In this paper, we propose to enrich the filter with additional refinement steps to abridge its sub-optimality. We test the proposed approach in two different

In this paper, we present a novel distributed task-allocation algorithm, namely the Sequential Task Addition Distributed Assignment Algorithm (STADAA), for autonomous multi-robot systems. The proposed STADAA can implemented in applications such as search and rescue, mobile-target tracking, and Intelligence, Surveillance, and Reconnaissance (ISR) missions. The proposed STADAA is developed by modifying

A major task in motion planning is to find paths that have a high ability to react to external influences while ensuring a collision-free operation at any time. This flexibility is even more important in human-robot collaboration since unforeseen events can occur anytime. Such ability can be described as mobility, which is composed of two characteristics. First, the ability to manipulate, and second

Simultaneous Localization and Mapping is a fundamental problem in mobile robotics. However, the majority of Visual SLAM algorithms assume a static scenario, limiting their applicability in real-world environments. Dealing with dynamic content in Visual SLAM is still an open problem, with solutions usually relying on purely geometric approaches. Deep learning techniques can improve the SLAM solution

Social robots may soon be able to play an important role in expanding communication with the deaf. Based on the literature, adaptive user interfaces lead to greater user acceptance and increased teaching efficiency compared to non-adaptive ones. In this paper, we build a robotic architecture able to simultaneously adjust a robot’s teaching parameters according to both the user’s past and present performance

The Cooperative Localization (CL) problem considers the case where groups of robots aim to improve their overall localization by sharing position estimates within the team instead of using landmarks in the environment. Despite being a well-studied problem, very few works deal with the increased complexity when a very large number of robots is used, as is the case in robotic swarms. In this paper, we

In this work a vertically integrated fault-tolerant control scheme for fixed-wing Unmanned Aerial Vehicles (UAVs) is presented. At its core, an online approximate Trim Flight Envelope generator yields the motion constraints of the UAV. Given fault information, it remains always up-to-date in view of emerging faults. The controller stack comprises of Nonlinear Model Predictive Controllers for angular

Drivable area detection is one of the essential functions of autonomous vehicles. However, due to the complexity and diversity of unknown environments, it remains a challenge specifically on rough roads. In this paper, we propose a systematical framework for drivable area detection, including ground segmentation and road labelling. For each scan, the point cloud is projected onto two different planes

Incidents of hydraulic or oil spills in the oceans/seas or ports occur with some regularity during the exploitation, production and transportation of petroleum products. Immediate, safe, effective and environmentally friendly measures must be adopted to reduce the impact of the oil spill on marine life. Due to the difficulty to detect and clean these areas, semi-autonomous vehicles can make a significant

Intelligent unmanned robotic systems have recently gained popularity due to their ability to potentially explore inaccessible and dynamically changing environments. In these environments, these vehicles might be subjected to unique types of disturbances that may lead to mission performance degradation. This paper describes the design, development and proof of concept of a novel adaptive control that

To improve the maneuverability of remotely guided quadrotors in longitudinal motion, the design goal of independent control of the horizontal and the vertical velocity, is satisfied. For the sake of the communication delays, a synchronization / signal reconstruction algorithm, imposing constant delays, is applied and the design goal is satisfied by introducing a stepwise safe switching procedure for

A novel path planning approach based on the bifurcation theory is proposed for a quadrotor UAV to track a ground vehicle in motion. For this purpose, a brief description of the mathematical model of the quadrotor UAV and the ground vehicle is presented, and the Hopf bifurcation method around a mobile balance point is used to design the path planning for a quadrotor UAV, and autonomously it generates

The parallel robots exhibit some outstanding properties on the repeatability, stiffness and force-to-weight ratio compared with serial robots. 6-DOF parallel robots have been utilized in various applications and the research on control design has attracted the attentions of researchers. However, the current Cartesian space path tracking performance of the parallel robots cannot meet the growing requirements

Over the last few decades, the appearance of robot applications has been continuously increasing in rehabilitation treatment due to the increasing numbers of stroke patients. In this paper, a novel fractional-order active fault-tolerant controller (FOAFTC) based on an adaptive nonlinear observer is proposed to detect, estimate, and compensate faults of a knee joint orthosis. The controlling term is

This paper proposes a modular system of precision agriculture to automate sprayers, optimizing the application of pesticides through a robotic system based on computer vision and individual nozzle on/off control. The system uses low-cost equipment such as Arduino boards, solenoid valves, pressure and flow sensors, smartphone, webcam, and Raspberry Pi. The motivation is to reduce the amount of pesticides

Online step adaptation is critical for legged locomotion to resist disturbances, while current approaches mainly focus on step location regardless of step timing. This paper proposes an online adaptation algorithm that deals with both step timing and step location. A model predictive control framework is developed based on centroidal dynamics to predict robot state trajectories, which are utilized

Behavior Trees (BTs) have received increasing popularity in the robotics community, serving as an efficient way of modeling robot behavior and structuring behavior interactions. Utilizing automated planning with BT task-level robot control has been proven efficiently reactive to environment dynamics, allowing iterative expansion of BT action nodes while executing the tree. However, existing BT-based

In recent years, UASs have become more and more popular. There are many reasons for this; one of the most popular is the enhancement of drones’ functionalities and improvement in battery life, stabilization, navigation, sensor technology, and much more. Many benefits drive growth. However, as the number of drones is expanding and their technological functionalities are evolving, drones’ use brings

We have developed and demonstrated an intelligent auto-organizing aerial robotic sensor network system composed of cameras installed on UAVs and ground fixtures for urban surveillance using the decentralised control paradigm. The system can auto-organize to meet user requirements, changes to user requirements and when new UAVs or ground cameras are added or are lost due to failure. User designated

With advances in science and technology, several innovative researches have been developed trying to figure out the main problems related to children’s learning. It is known that issues such as frustration and inattention, between others, affect student learning. In this fashion, robotics is an important resource that can be used towards helping to solve these issues, empowering our students in order

Microscopic analysis of microparticles in situ in diverse water environments is necessary for monitoring water quality and localizing contamination sources. Conventional sensors such as optical microscopes and fluorometers often require complex sample preparation, are restricted to small sample volumes, and are unable to simultaneously capture all pertinent details of a sample such as particle size

This paper provides a study of two deep reinforcement learning techniques for application in navigation of mobile robots, one of the techniques is the Soft Actor Critic (SAC) that is compared with the Deep Deterministic Policy Gradients (DDPG) algorithm in the same situation. In order to make a robot to arrive at a target in an environment, both networks have 10 laser range findings, the previous linear

Robotic soccer simulation is a challenging area, where the development of new techniques is paramount to remain competitive. Robotic skill evolution has accelerated with recent developments in deep learning algorithms, leading to improvements in behavior number and complexity. Shooting a ball towards a defined target is one of the most basic yet indispensable skills in soccer. However, fast and accurate

The hexapod robot is one of the important classes in legged robots due to its great potential to operate in complex settings with high stability and flexibility. However, few researches have investigated the navigation and autonomous locomotion of this type of robot. This paper concerns with the behavior-based control and navigation of an autonomous hexapod robot utilizing a hybrid automaton. Switching

This study proposes a coordinated path following approach to solve the formation reconfiguration problem in a guided manner. A novel coordinated path following control law is proposed, which steers a fleet of UAVs towards their closest projection points on their respective paths by controlling the angular velocity of each UAV, and achieves coordinated formation reconfiguration by synchronizing the

Speed and separation monitoring (SSM) is one of the four permissible collaborative operations in human-robot interaction (HRI). At all times, it must be ensured that the speed-dependent separation distance is maintained. To guarantee this, the robot speed or the robot path can be adapted. In this paper, the robot speed adaption for multiple trajectories is implemented in an HRI simulation tool and

We present a multirotor Unmanned Aerial Vehicle (UAV) control and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments

This study proposes a drone-based delivery schedul- ing method considering drone failures to minimize the expected loss of demand (ELOD). An optimization model (DDS-F) is developed to determine the assignment of each drone to a subset of customers and the corresponding delivery sequence. Because solving the optimization model is computationally challenging, a Simulated Annealing (SA) heuristic algorithm