A great amount of effort has been devoted to the study on self-separation assurance approach for civil aviation in the airspace with increasing density. In this article, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is modified to make it work for autonomous and decentralized collision avoidance for civil aircraft. Without considering the direction selectivity of collision-free maneuver

Pouring is one of the most commonly executed tasks in humans’ daily lives, whose accuracy is affected by multiple factors, including the type of material to be poured and the geometry of the source and receiving containers. In this work, we propose a self-supervised learning approach that learns the pouring dynamics, pouring motion, and outcomes from unsupervised demonstrations for accurate pouring

Aimed at the negative effect of dynamics characteristics of leg hydraulic drive system (LHDS) on the accuracy of motion control of the hydraulic drive legged robot, a dynamics compensation control method is proposed. First, according to the mechanical structure of LHDS, the kinematics and statics models of LHDS are analyzed and obtained respectively. Based on the principle of force-based impedance

The risk toward human lives in situations involving chemical, biological, radiological, and nuclear (CBRN) threats can be mitigated or even neutralized by deploying carrying a suite of suitable sensors. Furthermore, mobile robots open up the possibility for automated radiological field surveys and monitoring operations, which have important applications in scenarios with CBRN threats. A path planner

Efficient robotic behaviors require robustness and adaptation to dynamic changes of the environment, whose characteristics rapidly vary during robot operation. To generate effective robot action policies, planning and learning techniques have shown the most promising results. However, if considered individually, they present different limitations. Planning techniques lack generalization among similar

We present an experimental investigation of a multi-sensor fusion-learning system for detecting pedestrians in foggy weather conditions. The method combines two pipelines for people detection running on two different sensors commonly found on moving vehicles: lidar and radar. The two pipelines are not only combined by sensor fusion, but information from one pipeline is used to train the other. We build

This paper deals with the formation flying control problem for a team of nonlinear uncertain quadrotors in presence of noisy measurements and environmental disturbances. A novel distributed output-feedback nonlinear robust algorithm is proposed to solve the problem. The algorithm leads to a series of combined estimation-control local policies with minimum communicated information by decomposing the

Just like humans, robots can improve their performance by practicing, i. e. by performing the desired behavior many times and updating the underlying skill representation using the newly gathered data. In this paper, we propose to implement robot practicing by applying statistical and reinforcement learning (RL) in a latent space of the selected skill representation. The latent space is computed by

Autonomous mobile robots are becoming increasingly important in many industrial and domestic environments. Dealing with unforeseen situations is a difficult problem that must be tackled to achieve long-term robot autonomy. In vision-based localization and navigation methods, one of the major issues is the scene dynamics. The autonomous operation of the robot may become unreliable if the changes occurring

Search and find mission in ocean environment is a none trivial operation given the amount of random parameters associated with it. The uncertain and dynamic aspects related to ocean current movement make the trajectory prediction of drifting lost object onto sea water a very complicated task. In this work we present a novel lost target searching algorithm based on Recursive Area Clustering and target

This paper takes a novel look at formation control by comparing control setups based on two very different frameworks. These are applied to the distributed control of communicating omnidirectional mobile robots. One framework, which is possibly the most common approach to formation control, is based on algebraic graph theory, whereas the other, namely distributed model predictive control (DMPC), is

Magnetic actuation techniques and microrobots have attracted great interest since they have potential in biomedicine applications. Interventional techniques have emerged as a tool to handle a wide range of minimally invasive surgeries (MIS). However, current MIS procedures are constrained by the limitation of manual operation by surgeon. Thus, various microrobotic solutions including magnetic navigation

This paper presents an efficient multi-fingered grasping force optimization (GFO) method based on generalized penalty-function concepts. In view of the fact that the mainstream multi-fingered GFO method often treats the second-order cone programming (SOCP) problem as a semi-definite programming (SDP) problem, whose computational complexity is high, we hereby use the barrier function to construct the

It is one of the great challenges for a robot to learn compliant movements in interaction tasks. The robot can easily acquire motion skills from a human tutor by kinematics demonstration, however, this becomes much more difficult when it comes to the compliant skills. This paper aims to provide a possible solution to address this problem by proposing a two-stage approach. In the first stage, the human

Research on unmanned aerial vehicles is growing as they are becoming less expensive and more available than before. The applications span a large number of areas and include border security, search and rescue, wildlife surveying, firefighting, precision agriculture, structure inspection, surveying and mapping, aerial photography, and recreative applications. These applications can require autonomous

Robustly estimating the orientations of people is a crucial precondition for a wide range of applications. Especially for autonomous systems operating in populated environments, the orientation of a person can give valuable information to increase their acceptance. Given people’s orientations, mobile systems can apply navigation strategies which take people’s proxemics into account or approach them

An environment cannot be effectively described with a single perception form in skill learning for robotic assembly. The visual perception may provide the object’s apparent characteristics and the softness or stiffness of the object could be detected using the contact force/torque information during the assembly process. In the process of inserting assembly strategy learning, most of the work takes

This report describes an automatic control system that allows an assistive robot pushing a wheelchair to climb steps. The robot is equipped with a wheeled mechanism and dual manipulators. The wheelchair is a commercially available model that has been equipped with sensors, circuits, and batteries. The robot and wheelchair are connected when the vehicles climb a step. In that operation, the front wheels

Animals learn to master their capabilities by trial and error, and with out having any knowledge about their dynamics model and mathematical or physical rules. They use their maximum capabilities in an optimized way. This is the result of millions of years of evolution where the best of different possibilities are kept, and makes us rethink How does the nature perform things?, particularly when natural

Dynamics performance is very important for a manipulator used for high-speed machining. In this paper, the dynamic performance evaluation method of the 2UPU/SP parallel mechanism in a hybrid robot for aerospace composite machining is studied. The dynamic model is obtained by the virtual work principle, and a dynamic performance index considering gravity is proposed. Based on the given performance index

For effective verbal communication in collaborative tasks, robots need to account for the different perspectives of their human partners when referring to objects in a shared space. For example, when a robot helps its partner find correct pieces while assembling furniture, it needs to understand how its collaborator perceives the world and refer to objects accordingly. In this work, we propose a method

The collision-free navigation of a mobile robot in clutter environments is challenging. Global Positioning System (GPS) and adaptive neuro-fuzzy inference system (ANFIS) are well-known techniques widely used for navigation and control, respectively. This paper proposes a hybrid GPS-ANFIS based method for collision-free navigation of autonomous mobile robots. The GPS-based controller keeps the navigation

Anticipation of human movements is of great importance for service robots, as it is necessary to avoid interferences and predict areas where human–robot collaboration may be needed. In indoor scenarios, human movements often depend on objects with which they interacted before. For example, if a human interacts with a cup the probability that a table or coffee machine might be the next navigation goal

One of the problems that service robotics deals with is to bring mobile manipulators to work in semi-structured human scenarios, which requires an efficient and flexible way to execute every-day tasks, like serve a cup in a cluttered environment. Usually, for those tasks, the combination of symbolic and geometric levels of planning is necessary, as well as the integration of perception models with

The achievement of adaptive, stable, and robust locomotion and dealing with asymmetrical conditions for bipedal robots remain a challenging problem. To address the problem, this paper introduces adaptive parallel reflex- and decoupled central pattern generator (CPG)-based control for a planar bipedal robot. The control has modular structure consisting of two parallel modules that work together. Firstly

We propose a methodology for lidar super-resolution with ground vehicles driving on roadways, which relies completely on a driving simulator to enhance, via deep learning, the apparent resolution of a physical lidar. To increase the resolution of the point cloud captured by a sparse 3D lidar, we convert this problem from 3D Euclidean space into an image super-resolution problem in 2D image space, which

The FastSLAM is a typical tracking algorithm for SLAM, but it often suffers from the low tracking accuracy. To mitigate the problem, an improved H-Infinity unscented FastSLAM (IHUFastSLAM) with adaptive genetic resampling is proposed in this paper. Specifically, the H-Infinity unscented Kalman filter algorithm is improved using an adaptive factor and is employed as importance sampling in particle filter

The evolution of Intelligent Transportation Systems in recent times necessitates the development of self-awareness in agents. Before the intensive use of Machine Learning, the detection of abnormalities was manually programmed by checking every variable and creating huge nested conditions that are very difficult to track. This paper aims to introduce a novel method to develop self-awareness in autonomous

This paper presents a rapid (real time) solution to the minimum-time path planning problem for Dubins vehicles under environmental currents (wind or ocean currents). Real-time solutions are essential in time-critical situations (such as replanning under dynamically changing environments or tracking fast moving targets). Typically, Dubins problem requires to solve for six path types; however, due to

Understanding of the driving scenario represents a necessary condition for autonomous driving. Within the control routine of an autonomous vehicle, it represents the preliminary step for the motion planning system. Estimation algorithms hence need to handle a considerable number of information coming from multiple sensors, to provide estimates regarding the motion of ego-vehicle and surrounding obstacles

This study proposes a new shared mixed reality (MR)-bilateral telerobotic system. The main contribution of this study is to combine MR teleoperation and bilateral teleoperation, which takes advantage of the two types of teleoperation and compensates for each other’s drawbacks. With this combination, the proposed system can address the asymmetry issues in bilateral teleoperation, such as kinematic redundancy

Parallel continuum robots get their compliance and compactness from continuum rods while also having the stability and strength of parallel robots. Their potential to provide multi-degree-of-freedom articulation gives them versatility and makes them very useful in various applications. The purpose of this paper is to model a six link parallel continuum robot using the Cosserat theory. The single rod

Building 3D maps of various terrains is a necessary approach to gain environmental information for mobile robots when they are exploring in unknown territories. In this paper, we propose a method to construct a point cloud map with laser-measured data as the robot moves around. A terrain-adaptive density mapping technique is used to balance the demands of small data size and high terrain accuracy by

Humanoid robots generated by inspiring by human appearances and abilities have became essential in human society to improve the quality of their life. All over the world, there have been many researchers who have focused on humanoid robots to develop the capabilities of humanoid robots. Generally, humanoid robot systems include mechanisms of decision making and information processing. Because of the

In this paper, we study Emergency Landing Aware Surveillance Planning (ELASP) to determine a cost-efficient trajectory to visit a given set of target locations such that a safe emergency landing is possible at any point of the multi-goal trajectory. The problem is motivated to guarantee a safe mission plan in a case of loss of thrust for which it is desirable to have a safe gliding trajectory to a

This paper presents a multi-task instance segmentation neural network able to provide both road lane and road participants detection. The multi-task approach, ERFNet-based, allows feature sharing and reduces the computational requirements of the overall detection architecture, allowing real time performance even in configurations with limited hardware. The proposed method includes an ad-hoc training

Pattern formation for multi-robot systems has received increasing attention in different scenarios. However, existing methods cannot efficiently optimize pattern formation in the obstacle environment. To address this limitation, this paper proposes a new planning method that assigns the optimal goals to the robots and iteratively computes collision-free paths to reach goal positions. Firstly, according

This paper continues the previous effort on the development of a trajectory generation platform that assures minimum-control expenditure and collision-free manoeuvre of a torpedo-shaped autonomous underwater vehicle (AUV) into a funnel-shaped stationary docking station (DS). The earlier-developed guidance system was based on the Inverse Dynamics in the Virtual Domain (IDVD) method accounting for AUV’s

The recognition of previously visited places, known as Loop Closure Detection (LCD), composes one of the problems widely studied in robotics: simultaneous localization and mapping (SLAM). In this paper we propose a three level hierarchy based LCD method. In our serialized approach, in the First Level, a sequence of the most recently visited places is used as query to search for candidate sequences

Exploration is a task in which autonomous mobile robots incrementally discover features of interest in initially unknown environments. We consider the problem of exploration for map building, in which a robot explores an indoor environment in order to build a metric map. Most of the current exploration strategies used to select the next best locations to visit ignore prior knowledge about the environments

In crowded multi-agent navigation, the motion of the agents is significantly constrained by the motion of the nearby agents. This makes planning paths very difficult and leads to inefficient global motion. To address this problem, we propose a distributed approach, which we call C-Nav, that introduces politeness into multi agent navigation. With our approach, agents take into account the velocities

The daily working hours of mobile robots are limited primarily by battery life. Most systems use a combination of thresholds and fixed periods to decide when to charge. This produces charging behaviour that ignores high-value tasks that must be performed within time-windows or by deadlines. Instead the robot should schedule charging adaptively, taking into account the times of day when it is expected

Assist-as-needed control strategy is an emerging approach to improve the effectiveness of gait rehabilitation training. We have proposed a pneumatic muscle (PM) driven Gait Rehabilitation Exoskeleton (GAREX) implemented with a multi-input–multi-output (MIMO) sliding mode control system to actively adjust the assistance level provided during gait rehabilitation. To realize the assist-as-needed control

Combining model-based and model-free learning systems has been shown to improve the sample efficiency of learning to perform complex robotic tasks. However, dual-system approaches fail to consider the reliability of the learned model when it is applied to make multiple-step predictions, resulting in a compounding of prediction errors and performance degradation. In this paper, we present a novel dual-system

This paper presents three fault-tolerant control (FTC) strategies for a coaxial octorotor unmanned aerial vehicle (UAV) regarding motor failures. The first FTC is based on a control mixing strategy which consists of a set of control laws designed offline, each one dedicated to a specific fault situation. The second FTC, a robust adaptive sliding mode control allocation is presented, where the control

We present an approach for recognizing objects present in a scene and estimating their full pose by means of an accurate 3D instance-aware semantic reconstruction. Our framework couples convolutional neural networks (CNNs) and a state-of-the-art dense Simultaneous Localization and Mapping (SLAM) system, ElasticFusion (Whelan et al., 2016), to achieve both high-quality semantic reconstruction as well

We present a Visual Place Recognition (VPR) pipeline that achieves substantially improved precision as compared with approaches commonly appearing in the literature. It is based on a standard image retrieval configuration, with an initial stage that retrieves the closest candidates to a query from a database and a second stage where the list of candidates is re-ranked. The latter is realized by the

High dimensional robot motion planning has recently been approached with trajectory optimization methods that efficiently minimize a suitable objective function in order to generate robot trajectories that are both optimal and feasible. However, finding a globally optimal solution is often an insurmountable problem in practice and state-of-the-art trajectory optimization methods are thus prone to local

In this study, we present a novel concept of a multi tethered drone system. The system includes an arbitrary number of drones connected serially to an active ground station. The considered drones are of quadrotor type. Utilizing a unique pulley–gimbal mechanism, each drone can freely move along the tether, and its state is measured with respect to the ground station without the use of standard onboard

In this paper, we propose a new formulation to consider visual–spatial attention in order to improve the comfort of a human standing or operating near a collaborative robot. This formulation is based on the principle of having the robot’s end-effector in the human visual–spatial attention as much as possible. The integration of this new constraint into the Inverse Kinematics (IK) problem is thoroughly

Drone racing is becoming a popular sport where human pilots have to control their drones to fly at high speed through complex environments and pass a number of gates in a pre-defined sequence. In this paper, we develop an autonomous system for drones to race fully autonomously using only onboard resources. Instead of commonly used visual navigation methods, such as simultaneous localization and mapping

Advanced Driver Assistance Systems (ADAS) and Automated and Autonomous Vehicles (AV) are cooperative systems and processes that use: artificial intelligence, cognitive methods, cloud technologies, cooperative vehicle-to-everything-communications (V2X), software–hardwareplatforms, sensor platforms and incipient intelligent transport infrastructures, to get self-driving systems and smart connected mobility

This paper introduces a mobile robot with a new type of transformable wheel legs that can be used for flat and rough terrain. It integrates the stability and maneuverability of a wheeled robot and the legged robot’s obstacle climbing capacity using a transformable mechanism with wheel legs. With a transformation structure based on a four-bar mechanism, these two modes can be easily changed. This paper

This paper presents a novel challenging dataset that offers a new landscape of testing material for mobile robotics, autonomous driving research, and forestry operation. In contrast to common urban structures, we explore an unregulated natural environment to exemplify sub-urban and forest environment. The sequences provide two-natured data where each place is visited in summer and winter conditions

Recently, there have been several studies on the research and development of service robots, such as reception or waiter robots for facilities and companion robots for support of baggage transportation or guidance in public spaces. Several experimental results in real environments have been reported. To realize socially acceptable human–robot interaction for service robots, human recognition, including

So far, gas leakage caused by natural or human factors has led to serious consequences in terms of social security. Previous strategies for locating the odor sources appear to be either defective or incomplete. For enhancing the success rate and rapidity, this paper aims to present a novel and complete strategy in search of lurking gas sources. Particle filtering and information entropy are both employed