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

Despite many research studies focus on strategies to improve autopilot capabilities and bring artificial intelligence onboard Unmanned Aircraft Systems (UAS), there are still few experimental activities related to these vehicle performance under unconventional weather conditions. Air temperature and altitudes directly affect thrust and power coefficients of small scale propeller for UAS applications

Energy is a key feature that must be explicitly managed for long-term autonomous robotic missions. Many research studies have addressed the energy issue, developed energy-aware motion control or integrated energy in mission objectives. However, few studies have comprehensively assessed the impact of software and hardware choices on power consumption of robots. Based on experimental analysis and according

Obstacle map estimation based on efficient semantic segmentation networks is promising for improving the environmental awareness of unmanned surface vehicles (USVs). However, existing networks perform poorly in challenging scenes with small obstacles, scenery reflections, boat wakes, and visual ambiguities caused by unfavorable weather conditions. In this paper, we address the small obstacle segmentation

There are several compelling reasons for airlines to consider single pilot operations including economic savings, coping with a shortage of pilots, and automation and artificial intelligence technology advancement. To adequately explore this concept, differing aviation industry views of single pilot operations (SPO), challenges associated with single pilot operations, an overview of current SPO research

The majority of efforts in the field of sim-to-real Deep Reinforcement Learning focus on robot manipulators, which is justified by their importance for modern production plants. However, there are only a few studies for a more extensive use in manufacturing processes. In this paper, we contribute to this by automating a complex manufacturing-like process using simulation-based Deep Reinforcement Learning

This paper proposes a learning framework for Educational Robotics named sBotics, which includes a complete environment for teaching and programming skills acquisition designed for both teachers and K-12 students. Our framework has been developed using a gamified approach with the system and simulated environment developed in the Unity game engine. The main novelty of this platform is its ease-of-use

This paper proposes a formulation of quaternion-based Extended Kalman Filter pose estimation for six degrees of freedom systems embedded in an FPGA with commercial processors. Our approach uses the fusion of a camera and an inertial measurement unit to estimate simultaneously the position and the orientation of the system of interest. In addition, a Stewart platform is used to validate and evaluate

This work considers the anti-disturbance model reference L2-\(L_{\infty }\) control for the helicopter slung load system subject to unknown disturbances. Initially, a linear model is derived based on the nonlinear dynamics of a helicopter with slung load. The uncertainty and disturbances are jointly considered in the controller design. Then, by designing a disturbance observer and using robust L2-\(L_{\infty

In the control systems community, path-following refers to the problem of tracking an output reference curve. This work presents a novel model predictive path-following control formulation for nonlinear systems with constraints, extended with an obstacle avoidance strategy. The method proposed in this work simultaneously provides an optimizing solution for both, path-following and obstacle avoidance

This paper introduces a passivity-based control framework for multi-task time-delayed bilateral teleoperation and shared control of kinematically-redundant robots. The proposed method can be seen as extension of state-of-the art hierarchical whole-body control as it allows for some of the tasks to be commanded by a remotely-located human operator through a haptic device while the others are autonomously

The excellent swimming performances of live fish motivate scientists and engineers around the world to study its swimming mechanism and develop fish-like underwater robots, namely, the biomimetic robotic fishes. This paper compares different designs of biomimetic robotic fishes performing Body and/or Caudal Fin (BCF) swimming locomotion, and stresses how the designs evolve. The general trend is to

Because of complex and strong coupling system, the precision and adaptability of underground robots are greatly restricted. Based on the newly developed intelligent underground heavy-load robot which is still a gap to fill in current coal mine machinery, this paper proposes a new dynamic cooperative optimization control algorithm. Firstly, the complex and strongly coupled Multi-disciplinary Design

There are many potential applications of swarm robotic systems in real-world scenarios. In this paper, formation-containment controller design for single-integrator and double-integrator swarm robotic systems with input saturation is investigated. The swarm system contains two types of robots—leaders and followers. A novel control protocol and an implementation algorithm are proposed that enable the

In the field of unmanned aerial vehicles (UAVs), quadrotors are receiving considerable attention because of their potential application to industries such as transportation, inspection, and search and rescue. One of the key challenges is to robustly control the position and attitude of a UAV amid the mass and inertia uncertainties, as well as the external disturbances, that exist in the real environment

Recently, Multi-Robot Systems (MRS) have attained considerable recognition because of their efficiency and applicability in different types of real-life applications. This paper provides a comprehensive research study on MRS coordination, starting with the basic terminology, categorization, application domains, and finally, give a summary and insights on the proposed coordination approaches for each

The importance of the human upper limb role in performing daily life and personal activities is significant. Improper functioning of this organ due to neurological disorders or surgeries can greatly affect the daily activities performed by patients. This paper aims to comprehensively review soft and rigid wearable robotic devices provided for rehabilitation and assistance focusing on the shoulder joint

Traditional robot programming is often not feasible in small-batch production, as it is time-consuming, inefficient, and expensive. To shorten the time necessary to deploy robot tasks, we need appropriate tools to enable efficient reuse of existing robot control policies. Incremental Learning from Demonstration (iLfD) and reversible Dynamic Movement Primitives (DMP) provide a framework for efficient

The use of multirotor drones for industrial applications is accelerating, and fuel cell based propulsion systems are highlighted as a promising approach to improve endurance – one of the current main limitations. Due to multirotor drones’ unique requirements, careful system design is needed to maximize the performance advantage. In this work a sensitivity analysis that quantifies the impact of central

Safe landing in crowded areas is a crucial task for the successful integration of Unmanned Aerial Vehicles in common civilian applications. In this work, we propose a lightweight algorithm for identifying safe landing regions to prevent hurting people in emergency landing situations. To do so, a lightweight convolutional neural network architecture is developed to perform crowd detection and counting

Place recognition is an essential task in many robotics applications. Recognizing if the robot is crossing an already visited place may be used to improve its localization and map estimation. A place recognition strategy must be as accurate as possible, despite the challenges related to environment dynamicity. It should avoid generating false positives since even a few erroneous matches may be enough

This paper presents a displacement based collaboration strategy to carry a payload greater than the robot’s limit and transport it to a desired location through a planar cum obstacle-clustered environment using a multi-robot system. The proposed model has no explicit communication between the robots but it is verified that local measurements received from the payload’s motion data can be used as implicit

Enabling fully autonomous robots capable of navigating and exploring large-scale, unknown and complex environments has been at the core of robotics research for several decades. A key requirement in autonomous exploration is building accurate and consistent maps that can be used for reliable navigation. In this paper, we present a degeneracy-aware and drift-resilient loop closing method to improve

In this paper, an event-Mixed Integer Linear Programming (MILP)-based algorithm is proposed to solve the task allocation problem in a Robotic Sensor Network (RSN). A fleet of two types of vehicles is considered, giving, as a result, a heterogeneous configuration of the network, since each type of vehicle has a nominal velocity and a set of allowed paths to go. The algorithm can be applied to the distributed

A Correction to this paper has been published: https://doi.org/10.1007/s10846-021-01350-0.

Intuitive interaction is the cornerstone of accurate and effective performance in remote robotic teleoperation. It requires high-fidelity in control actions as well as perception (vision, haptic, and other sensory feedback) of the remote environment. This paper presents Vicarios, a Virtual Reality (VR) based interface with the aim of facilitating intuitive real-time remote teleoperation, while utilizing

The main goal in task planning is to build a sequence of actions that takes an agent from an initial state to a goal state. In robotics, this is particularly difficult because actions usually have several possible results, and sensors are prone to produce measurements with error. Partially observable Markov decision processes (POMDPs) are commonly employed, thanks to their ability to model the uncertainty

This paper revisits system identification and shows how new paradigms from machine learning can be used to improve it in the case of non-linear systems modeling from noisy and unbalanced dataset. We show that using importance sampling schemes in system identification can provide a significant performance boost in modeling, which is helpful to a predictive controller. The performance of the approach

Obstacle avoidance for Dynamic Movement Primitives (DMPs) is still a challenging problem. In our previous work, we proposed a framework for obstacle avoidance based on superquadric potential functions to represent volumes. In this work, we extend our previous work to include the velocity of the system in the definition of the potential. Our formulations guarantee smoother behavior with respect to state-of-the-art

This paper addresses the problem of multi-sensor fusion and estimation for a system composed of several collaborative subsystems. A multi-sensor fusion approach based on the Kalman filter and the covariance intersection algorithm is proposed. Moreover, centralized and distributed architectures are presented and discussed—the breakdown of calculation burdens on each system component is determined. The

In the aftermath of radiation or chemical accidents, responders must rapidly map out regions of contamination as quickly and accurately as possible. One important and relevant statistical method for this kind of disaster response is spatial kriging, which makes predictions based on incomplete knowledge of spatially referenced observations. Given an Unmanned Aerial System (UAS) equipped with radiation

Robotic manipulators are nonlinear systems that are extensively used in industrial applications to perform many complex and specialized tasks which requires high precision and accurate trajectory tracking. This paper proposes the real-time implementation of a Robust Discontinuous Controller Algorithm to achieve trajectory tracking for a 5 degrees of freedom (DOF) robotic manipulator in a fast and accurate

Compared to standard solutions, soft robotics presents enhanced adaptability to unpredictable and unstructured environments, encompassing advances in fabrication, modeling, and control. The absence of a general theory for the latter is one of the biggest challenges in the field, which constrains these robots’ employment in real-world applications. This research proposes the application of Scheduling

Robust localization is critical for the navigation and control of mobile robots. Global Navigation Satellite Systems (GNSS), Visual-Inertial Odometry (VIO), and Simultaneous Localization and Mapping (SLAM) offer different methods for achieving this goal. In some cases however, these methods may not be available or provide high enough accuracy. In such cases, these methods may be augmented or replaced

Visual simultaneous localization and mapping (V-SLAM) has attracted a lot of attention lately from the robotics communities due to its vast applications and importance. This paper addresses the problem of V-SLAM with points and lines in particular scenes where there are many lines on an approximately planar ground. All the lines in these particular scenes are treated as 3D lines with four degree-of-freedom

This paper addresses a challenging problem to achieve energy-saving autonomous homing to the desired target for a parafoil/rocket system with high-altitude. The system is subject to external unknown crosswind disturbance during the process. A novel optimal multiphase homing algorithm with high-altitude considering constant wind is first presented. To reduce the time-varying wind disturbance, an improved

Autonomous mobile devices operating in confined environments, such as pipes, underground tunnel systems, and cave networks, face multiple open challenges from the robotics perspective. Those challenges, such as mobility, localization, and mapping in GPS denied scenarios, are receiving particular attention from the academy and industry. One example is the Brazilian mining company Vale S.A., which is

Conventionally, the arm and the hand are considered separately for robotic manipulation and grasp. The hand configuration and the wrist pose are obtained during grasp planning and afterwards, the arm configuration is found to accommodate the wrist pose. However, without considering the arm during grasp planning, this approach can become very inefficient as significant time and computation power are

In this paper, an Inverse Kinematics (IK) algorithm combining the analytical method and the numerical one is proposed to solve the IK problem of a 7-DOF spraying robot with 4R 3-DOF non-spherical wrist. Firstly, the 7-DOF spraying robot is transformed into a 7-DOF robot with 3R spherical wrist and the arm angle is used as the redundancy parameter. The approximate IK solution is calculated analytically

Path planning and formation control are two of the most significant concepts which can be considered in multi-vehicle systems and particularly in autonomous underwater vehicles (AUVs). The cooperative implementation of complicated commands would lead to desirable results and increase the probability of success in the missions. Due to the nonlinear dynamics and environmental conditions, the cooperative

This paper proposes a guidance system with a new hybrid architecture for multiple fixed-wing unmanned aerial vehicles (UAVs) formation flight. The proposed architecture is hybrid in the sense of combining two control policies found in guidance systems: the Decentralized Partially Observable Markov Decision Process (Dec-POMDP) policy and the well-known PID controller. The Dec-POMDP policy part enables

The flight dynamics of Micro Air Vehicles (MAVs) exhibit significant nonlinear characteristics, which cannot be ignored in simulation or analysis. In this study, a full nonlinear simulation of the flight dynamics characteristics of a fixed-wing MAV is performed. To strengthen the developed nonlinear mathematical modeling, the MAV’s mass properties and propulsion characteristics are experimentally investigated

In the recent past, we have witnessed the adoption of different machine learning techniques for indoor positioning applications using WiFi, Bluetooth and other technologies. The techniques range from heuristically derived hand-crafted feature-based traditional machine learning algorithms, feature selection algorithms to the hierarchically self-evolving feature-based Deep Learning algorithms. The transient

Applications involving Unmanned Aerial Vehicles (UAVs) have increasingly required faster and more accurate movements to reduce flight time and to improve efficiency in the obstacle avoidance capability. In this context, this work proposes a nonlinear model predictive control (NMPC) strategy formulated on the Special Euclidean group SE(3) for quadrotor trajectory tracking within cluttered environments

We propose an evaluation framework that emulates poor image exposure conditions, low-range image sensors, lossy compression, as well as noise types which are common in robot vision. We present a rigorous evaluation of the robustness of several high-level image recognition models and investigate their performance under distinct image distortions. On one hand, F1 score shows that the majority of CNN

This work provides a deeper comparison between two path planning algorithms, the Dynamic Visibility Graph A Star (DVG+A*) and Rapidly–exploring Random Trees (RRT), when applied in a high dimension and dynamic environment, which is the RoboCup Small Size League. The algorithms were compared under two different perspectives. In the first analysis, the algorithms were evaluated according to its computational

In this paper, a robust position and attitude tracking control problem of a quadrotor subject to system nonlinearities, input coupling, aerodynamic uncertainties and external wind disturbances is investigated. An uncertainty and disturbance estimator (UDE) based robustified nonlinear dynamic inversion (NDI) control scheme is proposed for the purpose. The UDE technique robustifies the NDI based controller

The visual-inertial navigation system using a single camera and IMU requires an accurate initialization without increasing the processing cost and complexity for real-time deployment. The processing cost in the existing solutions can be traced to the gyroscopic bias estimation using 1) Closed-form solutions (Martinelli, Int. J. Comput. Vis. 106(2), 138–152, 2014; Kaiser et al., IEEE Robot. Autom. Lett

This paper presents a Model Predictive Control (MPC) based autopilot for a fixed-wing Unmanned Aircraft Vehicle (UAV) for meteorological data sampling tasks, named Aerosonde. Aerosonde missions are featured by predetermined operating conditions, allowing the design of ad-hoc controllers for each control task by using the future knowledge of the reference signals driving the aircraft during operations

The full-wing solar-powered unmanned aerial vehicle (UAV) adopts a large aspect ratio wing, a lightweight structural design, and a differential throttle control scheme to maximize flight endurance. Large structural deformation often occurs when the wing is heavily loaded, which affects its flight stability, trajectory tracking accuracy, and flight performance. The traditional rigid-body flight dynamics

Twin-rotor two-input two-output (TITO) aerodynamical system (TRAS) is a highly non-linear system with a cross-coupling effect. The objective of the controller design in TRAS is to track the trajectory of azimuth and pitch angles, reach the desired azimuth and pitch angle positions, and stabilize TRAS in the presence of significant cross-coupling. The coupling effect between the main rotor and tail

Object detection techniques that achieve state-of-the-art detection accuracy employ convolutional neural networks, implemented to have lower latency in graphics processing units. Some hardware systems, such as mobile robots, operate under constrained hardware situations, but still benefit from object detection capabilities. Multiple network models have been proposed, achieving comparable accuracy with

A significant ongoing issue in realistic humanoid robotics (RHRs) is inaccurate speech to mouth synchronisation. Even the most advanced robotic systems cannot authentically emulate the natural movements of the human jaw, lips and tongue during verbal communication. These visual and functional irregularities have the potential to propagate the Uncanny Valley Effect (UVE) and reduce speech understanding

We present a design method for the admittance control of a class of omnidirectional mobile platforms. Holonomic behavior of the platform is accomplished by a steering system that is itself subject to nonholonomic constraints. The proposed application of this type of platform, henceforth the “walker”, is as an assistive device for human gait rehabilitation. Therefore, the control design objectives are

This work addresses the problem of mapping terrain features based on inertial and LiDAR measurements to estimate navigation cost, for an autonomous ground robot. The navigation cost quantifies the degree of how easy or difficult it is to navigate through different areas. Unlike most indoor applications, where surfaces are usually human-made, flat, and structured, external environments may be unpredictable