This paper introduces an enhancement to traditional sampling-based planners, resulting in efficiency increases for high-dimensional holonomic systems such as hyper-redundant manipulators, snake-like robots, and humanoids. Despite the performance advantages of modern sampling-based motion planners, solving high dimensional planning problems in near real-time remains a considerable challenge. The proposed

Real-time vision-based robotic grasping is challenging in clutter. In such scene, the target object should be perceived accurately, where it may be occluded and misrecognized by many distractors including irrelevant objects and the robotic arm. In addition, the limited field of view (FOV) of camera makes it prone for objects to get out of the camera view. We develop a novel camera fusion method of

In this work, we present an optimization-based trajectory tracking solution for multirotor aerial robots given a geometrically feasible path. A trajectory planner generates a minimum-time kinematically and dynamically feasible trajectory that includes not only standard restrictions such as continuity and limits on the trajectory, constraints in the waypoints, and maximum distance between the planned

In this article, the dynamic equations of a reconfigurable non-holonomic mobile robot used for space explorations and rescue operations are presented. Dimensions of mobile robots usually remain unchanged while they are programmed to determine a new path to bypass obstacles. The aim of developing this robot is to upgrade the mechanical structure so it can adapt its structure to pass the obstacles without

In this study, a hierarchical clustering matching (HCM) algorithm is proposed to match features with ambiguity due to repetitive patterns in visual odometry. Visual odometry is a real-time system that estimates the motions of camera setups, in which feature matching is a key step for tracking and relocalization. However, it is still difficult to remove outliers fast and reliably when a high proportion

This paper presents deployment strategies to achieve full visibility of 1.5D and 2.5D polyhedral environments for a team of mobile robots. Agents may only communicate if they are within line-of-sight. In 1.5D polyhedral terrains we achieve this by algorithmically determining a set of locations that the robots can occupy in a distributed fashion. We characterize the time of completion of the resulting

Cops and Robbers problems are classical examples of pursuit and evasion problems which are parts of key researches in the field of robotics. This study shall specifically focus on the evasion strategies of robbers. This study presents the receding horizon optimization method to obtain such strategies of robbers and solves the Cops and Robbers problems in a complex environment with obstacles. In this

Qualitative modeling allows autonomous agents to learn comprehensible control models, formulated in a way that is close to human intuition. By abstracting away certain numerical information, qualitative models can provide better insights into operating principles of a dynamic system in comparison to traditional numerical models. We show that qualitative models, learned from numerical traces, contain

Nowadays, robots equipped with a single camera, such as micro aerial vehicles (MAVs), are easily found at affordable costs. They can be used in different tasks, including the building of 3D environment maps. For building such maps, monocular simultaneous localization and mapping (SLAM) methods are employed, which usually generate sparse or semi-dense representations that are ill-suited for navigation

Emotions are important in many aspects of human behavior. Emotions are displayed on human faces, they are reflected in human memory, and they even influence human intelligence. The creation of robots that try to mimic humans arises the question of how the concept of emotion can be transferred to robots. There is no unique answer to the question, however many robots that leverage emotions exist. By

The research study aims to create a framework for autonomous control technology for unmanned aerial vehicles with real-time target-relative guidance capabilities, which leverages onboard decision-making to provide targeting and re-targeting solutions. Thus, this paper aims to develop extremal control and guidance functions in the context of the optimal control problem and their integration for applications

A novel robust control method for simultaneous position/force control of constrained flexible joint robots is proposed. The facts that the uncertainties make the usual control task unsolvable and that the equations of the controlled system are differential-algebraic make the problem dealt with considerably demanding. In order to overcome the unsolvability problem due to the constraint uncertainties

In this paper, we propose a new parcel delivery system consisting of a public train and drones. The train, an already existing mobile platform in our neighbourhood, follows its normal predefined route and timetable to transport passengers. In the meanwhile, some parcels to be delivered to some customers and a delivery drone are stored on its roof. The drone can launch from the train, deliver the parcel

This paper presents a trajectory planning framework to deal with the highly dynamic environments for on-road driving. The trajectory optimization problem with parameterized curvature control was formulated to reach the goal state with the vehicle model and its dynamic constraints considered. This in contrast to existing curve fitting techniques guarantees the dynamic feasibility of the planned trajectory

In this paper, we propose a novel curved path following scheme for multiple fixed-wing unmanned aerial vehicles (UAVs) that can achieve coordinated curved path following and handle collision avoidance simultaneously. The proposed solution is a hybrid system that combines a path following strategy and a collision avoidance method to ensure collision-free maneuvering of a group of UAVs cooperative flight

The odometry is an important part of intelligent mobile robots to achieve positioning and navigation functions. At present, the mainstream visual odometry locates only through the visual information obtained by camera sensors. Therefore, in the case of insufficient light, texture missing and camera jitter, the visual odometry is difficult to locate accurately. To solve the problem, we propose a binocular

This paper addresses the problem of cooperative manipulation and transportation of large and/or heavy unknown objects via a team of aerial robots. In particular, the chosen aerial platform is an omnidirectional quadrotor, which, by exploiting two additional actuators, has the capability to produce an omnidirectional total thrust by changing the orientation of the plane of the rotors. Since it is assumed

Nursing robots can be a good substitute to do nursing works for severely disabled patients who have completely lost the ability of movement. In order to improve the safety and comfort of human-robot interaction, we propose a novel compliant manipulation method for a nursing robot based on physical structure of human limb, which is applicable to severely disabled patients and can reduce the high performance

Modern unmanned aerial vehicles (UAVs) rely on high-frequency periodic sensor measurements in order to safely operate in cluttered environments with both static and dynamic obstacles. However, periodic sensor checking operations are time and computation consuming and they are often not needed, especially in situations where the UAV can operate without violating the safety constraint (e.g., in uncluttered

This paper presents the modeling, system identification, simulation and flight testing of the airbrake of an unmanned experimental aircraft in frame of the FLEXOP H2020 EU project. As the aircraft is equipped with a jet engine with slow response an airbrake is required to increase deceleration after speeding up the aircraft for flutter testing in order to remain inside the limited airspace granted

This paper proposes a method for real-time rerouting drone flights under uncertain flight times. The battery runtime that remains of a drone in real-time may be insufficient to complete its flight mission. This may be due to external factors, such as unexpected severe weather or obstacles that move into the drone’s flight path. Under unexpected situations, such as these, the drone cannot safely return

We address a cooperative transport control problem involving three or more unmanned aerial vehicles (UAVs). We realize the transportation of an object that cannot be carried with a small number of UAVs. To improve scalability and real-time performance, we propose a controller that does not require optimization calculations. The attitude and position of the transported object are controlled by contact

The propulsion subsystem of multi-rotor Unmanned Aerial Vehicles (UAV) is one of the most complex due to the aerodynamic, aero-elastic and electromechanical elements it comprises. Therefore, accurate models of this subsystem can be difficult to work with. Therefore, simplified models are normally used for the design of control and navigation algorithms. Considering this, the effectiveness of these

This work proposes the Drone Reconfigurable Architecture (\(\mathcal {DRA}\)), which is a modular architecture for UAVs with electrical, mechanical, and computational specifications. The theoretical aspects of the architecture are introduced through a case study with practical implementations aiming to design a multi-rotor UAV, which also includes the manufacturing steps of a functional prototype.

In this study, an image processing based indoor positioning system (IPS) scheme is presented. Real-time image of uniquely coded passive reflective tags which are illuminated by an infrared projector is used to calculate the instantaneous position of an object. The system simultaneously provides real-time position data and identifies unregistered tags and makes it possible to use these tags in later

Monocular depth estimation by unsupervised learning is a potential strategy, which is mainly self-supervised by calculating view reconstruction loss from stereo pairs or monocular sequences. However, most existing works only consider the geometric information during training, without using semantics. We propose a semantic monocular depth estimation (SE-Net), a neural network framework that estimates

Maps generated by many visual Simultaneous Localization and Mapping algorithms consist of geometric primitives such as points, lines or planes. These maps offer a topographic representation of the environment, but they contain no semantic information about the environments. Object classifiers leveraging advances in machine learning are highly accurate and reliable, capable of detecting and classifying

Visual odometry (VO) is one of the promising techniques that estimates pose using the camera and does not necessarily require other sensor aiding. With increasing automation and the use of miniaturized systems such as mobile devices, wearable gadgets, & gaming consoles, demand for efficient algorithms have risen. In this paper, an attempt is made to remove the redundant features from the VO pipeline

Learning to grasp novel objects is a challenging issue for service robots, especially when the robot is performing goal-oriented manipulation or interaction tasks whilst only single-view RGB-D sensor data is available. While some visual approaches focus on grasping that satisfy force-closure standards only, we further link affordances-based task constraints to the grasp pose on object parts, so that

Restricted mission capability becomes one of the most important challenges facing multicopter UAVs with the increasing complexity of the low-altitude remote sensing mission. Mission capability estimation is the major precondition and the foundation of the mission planning, decomposition, and execution. It’s constrained by platform performance, payload characteristics, mission requirements, and environmental

Evaluating unmanned aerial vehicle (UAV) survivability is crucial when UAVs are required to perform missions in hostile areas. There are complex spatiotemporal interactions among entities in hostile areas; therefore, evaluation of the survivability of a UAV flying along a specific route needs to effectively fuse spatiotemporal information. It is difficult to clarify how information is fused and how

Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe

In this paper, we investigate the problem of maximizing the manipulability index while solving a general Inverse Kinematics (IK) problem of a redundant industrial manipulator. Manipulability index has been extensively studied in the robotics literature and several formulae have been developed, nevertheless, they mainly only exploit the robot redundancy. The general IK is formulated as a Quadratic Programming

In areas that demand short-term Internet connectivity, like events and mobile offices, it is not feasible to have a permanent wireless Internet infrastructure. To provide broadband Internet access to temporary clients, we propose the use of flying networks. These networks need to be carefully managed, mainly due to the limitation on their nodes’ battery capacity. Considering these issues, we introduce

This article presents a general innovative technique for dynamically modeling and control of trajectory tracking in an industrial manipulator with multi-rigid links (connected by rotary-sliding (R-S) joints), which is installed on a non-holonomic moving platform on wheels. To accomplish this purpose, first the Gibbs-Appell (G-A) technique is used for getting the dynamic equations of the mentioned manipulator

A novel formation control to transport a cable-suspended payload with two quadrotors is presented. The control structure is based on a layered scheme combining a kinematic null-space based controller and a neural sliding mode controller. The null-space controller is designed to generate velocity references to the quadrotors in the formation, whereas the neural sliding mode controller receives such

In this work, we propose the integration of a bank of Discrete Generalized Proportional Integral Observers (DGPIO) within an Interacting Multiple Model (IMM) structure in order to improve the precision of visual-tracking tasks. Applications such as visual servoing, robotic assisted surgery and optronic weapon systems require accurate and high-precision measurements provided by real-time visual-tracking

Sensitivity Amplification Control (SAC) algorithm was first proposed in the augmentation application of the Berkeley Lower Extremity Exoskeleton (BLEEX). Since the SAC algorithm can greatly reduce the complexity of exoskeleton system, it is widely used in human augmentation applications. Nevertheless, the performance of the SAC algorithm depends on the accuracy of dynamic model parameters. In this

This paper introduces a dynamic path planning method for the UAV that can avoid both static and moving obstacles. The condition with sudden threats can better reflect the real situation of the UAV in the real environment. First of all, the A* algorithm is adopted to generate an optimal path in a known environment in this method. Then, in the situation of static sudden threats, a series of candidate

Autonomous underwater vehicles (AUVs) are robots that operate in underwater environment and do not need involvement of an operator when performing some tasks. In order to move independently in water environment, AUVs need navigation capabilities, on the one hand, they have to be able to detect obstacles and avoid them, and on the other hand, they also have to know their own position and spatial orientation

In the kinematic design of wearable exoskeletons, the issue of axis misalignments between the human and the exoskeleton joints should be well dealt with. Otherwise, large physical human-robot interaction (p-HRI) forces may occur at the human-robot interfaces, which makes the p-HRI uncomfortable or even unsafe. To cope with this issue, a kinematically compatible design approach of wearable exoskeletons

In this work, based on shaping an energy function, it is introduced an output-feedback regulation control law for a Planar Vertical Takeoff and Landing (PVTOL) aircraft. To this end, a version of the matching control energy method is used to construct the Lyapunov candidate function and the stabilizer controller to regulate the PVTOL aircraft. The non-measurable system velocities are recovered using

Mobile robots are frequently faced with mapping and exploring uncertain environments in surveillance, military, and convenience tasks. Often times, human teleoperation is either inconvenient or infeasible for these kinds missions. Furthermore, these tasks can be improved by cooperative multi-agent systems, where coordinating robotic efforts can be complicated and computationally-expensive. This paper

Path planning remains a challenge for Unmanned Aerial Vehicles (UAVs) in dynamic environments with potential threats. In this paper, we have proposed a Deep Reinforcement Learning (DRL) approach for UAV path planning based on the global situation information. We have chosen the STAGE Scenario software to provide the simulation environment where a situation assessment model is developed with consideration

In this paper, a novel technique is presented to test the flight of an unmanned aerial vehicle autonomously in a real-world scenario using a data-driven technique without intervening with its onboard software. With the growing applications of such vehicles, testing of autonomous flight is a very important task for rapid deployment. There are different tools for modeling and simulating unmanned vehicles

Socially acceptable navigation is a subject that involves developments regarding Human-Robot Interaction (HRI) and autonomous mobile robot navigation. In this context, there is little research considering people interacting with a robot team, and even fewer considering multi-robot teams with people. In this paper, a study on socially acceptable navigation involving a human and a robot team is presented

In this paper, we design an optimal control system for a quadrotor to carry a cable-suspended load flying through a window. As the window is narrower than the length of the cable, it is very challenging to design a practical control system to pass through it. Our solution includes a system identification component, a trajectory generation component, and a trajectory tracking control component. The

The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of

This paper presents an approach to the dynamic leader selection problem in autonomous non-holonomic mobile robot formations when the current leader enters a failure state. Our method is based on a tree structure coupled with a modified version of the Nonlinear Model Predictive Control (NMPC) that allows for behavior change at the controller level. An explanation of the control algorithm, behavior selection

This paper proposes a robust model predictive control (MPC) strategy for the trajectory tracking control of a four-mecanum-wheeled omni-directional mobile robot (FM-OMR) under various constraints. The method proposed in this paper can solve various constraints while implementing trajectory tracking of the FM-OMR. Firstly, a kinematics model with constraint relationship of the FM-OMR is established

Load transportation by quadrotors and similar aircrafts is a topic of great interest to the robotics community nowadays, most likely due to logistic gains for deliveries of commercial cargo. Aiming at being the first reading for novice researchers and graduate students, this survey highlights meaningful research works of several groups worldwide, considering two basic approaches, namely grasped and

In order to navigate an unknown environment, an autonomous robot must be able to build a map of its surroundings while estimating its position at the same time. This problem is known as SLAM. We propose a SLAM system for stereo cameras which builds a map of objects in a scene. The system is based on the SLAM method S-PTAM and an object detection module. The object detection module uses Deep Learning

In the context of multi-robot system and more generally for Technological System-of-Systems, this paper proposes a multi-UAV (Unmanned Aerial Vehicle) framework for SLAM-based cooperative exploration under limited communication bandwidth. The exploration strategy, based on RGB-D grid mapping and group leader decision making, uses a new utility function that takes into account each robot distance in

Environmental exploration is one of the common tasks in the robotic domain which is also known as foraging. In comparison with the typical foraging tasks, our work focuses on the Multi-Robot Task Allocation (MRTA) problem in the exploration and destruction domain, where a team of robots is required to cooperatively search for targets hidden in the environment and attempt to destroy them. As usual,

This paper deals with the visual regulation problem of wheeled mobile robots (WMRs) in the presence of uncalibrated camera-to-robot parameters and unknown image depth. A two-stage controller is designed by using a switching approach. Specifically, in the first stage, an invariant-manifold-based adaptive controller is presented to bring the lateral error and angular error within an arbitrarily small

In this research, two novel online fault detection algorithms are proposed for sensor faults in aircraft. Radial basis function neural network (RBFNN) is used as a fault detection technique, for weight updating parameters adaptive learning rates are used instead of fixed learning rates, two different adaptive learning rate strategies are proposed based on Lyapunov functions which are compared to Extended

This paper proposes a path planner for multi-robot systems based on the solution of the multiple traveling salesman problem by genetic algorithm. The main planning goal is to build an efficient path to each robot of the system which jointly ensures that several a priori known points (ways-points) in the environment can be attained by at least one of the robots. During navigation, each robot try to

Collision detection and avoidance are vital sub-tasks in any autonomous robotic task. This work presents a technique that guarantees collision avoidance in an environment containing multiple agents. These agents can be of different types such as static, dynamic obstacles and other robots. The technique supports parallel implementation and is appropriate for real-time applications. In this work, the

Underwater docking technology enables autonomous underwater vehicles (AUVs) to execute long-term observation missions by periodically recovering and recharging AUVs. The conventional AUV homing and docking operations utilize acoustic and optical sensors at different ranges relative to the docking station. However, this method cannot perform perfectly in confined water regions because of the acoustic

Abstract It is relevant to develop an adequate control algorithm for quadrotors that guarantees a good compromise robustness/ performance. This compromise should be ensured with or without external disturbances. In this paper, we investigate and apply a revisited formulation of a reference model-based control strategy by introducing a boosting mechanism. This mechanism uses an Extended State-based