Different high-level robotics tasks require the robot to manipulate or interact with objects that are in an unexplored part of the environment or not already in its field of view. Although much works rely on searching for objects based on their colour or 3D context, we argue that text information is a useful and functional visual cue to guide the search. In this paper, we study the problem of active

This article presents an approach for collision-free kinematics of multiple redundant manipulators in complex environments. The approach describes a representation of task space and joint limit constraints for redundant manipulators and handles collision-free constraints by micromanipulator dynamic model and velocity obstacles. A new algorithm based on Newton-based and first-order techniques is proposed

This paper provides details on best practices for vehicle design for BVLOS missions, with a focus on robust control links and real-time health monitoring.The development work presented herein focuses on a specific mission to set the speed and distance world record for a fully autonomous vehicle, requiring development of analytic tools for estimating vehicle range and endurance, as well as models for

In this study, we present a novel neural control architecture for gait adaptation and obstacle avoidance of a tailless gecko robot. The control architecture is based on a hierarchical modular structure, consisting of several neural layers and modules. The first layer contains three sensory preprocessing modules which filter sensory noise and generate appropriate descending commands to activate corresponding

Visual scene understanding and place recognition are the most challenging problems that mobile robots must solve for to achieve autonomous navigation. To reduce the high computational complexity of many global optimal search strategies, a new two-stage loop closure detection (LCD) strategy is developed in this paper. The front-end sequence node level matching (FSNLM) algorithm is based on the local

Calibration is a strategy to compensate for the systematic errors of a mobile robot hence, to increase the accuracy of the robot localization. So far, various methodologies have been proposed for the calibration of wheeled robots, but the majority have focused on non-holonomic mobile robots, e.g., differential type, and holonomic ones have been less studied from this point of view. This paper presents

A novel monocular visual simultaneous localization and mapping (SLAM) algorithm built on the semi-direct method is proposed to deal with some problems in complex environments, such as low-texture, moving objects and perceptual aliasing. The proposed algorithm takes advantage of direct and feature-based methods. On one hand, a direct method is used to track the camera poses and solve the feature alignment

To be able to recover a fixed-wing unmanned aerial vehicle (UAV) on a small space like a boat deck or a glade in the forest, a steep and precise descent is needed. One way to reduce the speed of the UAV during landing is by performing a deep-stall landing manoeuvre, where the lift of the UAV is decreased until it is unable to keep the UAV level, at the same time as the drag is increased to minimize

In this paper, an imitation learning approach of vision guided reaching skill is proposed for robotic precision manipulation, which enables the robot to adapt its end-effector’s nonlinear motion with the awareness of collision-avoidance. The reaching skill model firstly uses the raw images of objects as inputs, and generates the incremental motion command to guide the lower-level vision-based controller

The domain of robotics is successfully automating majority of terrestrial applications with significant breakthroughs in research involving wheeled robots. Robots equipped with biomimetic capabilities can aid effectively in many scenarios where conventional infrastructure such as roads, flat terrains and wheeled robots are not available. 2DxoPod is a modular robot developed with the aim improve the

In this paper, we address the problem of multiple quadcopter control, where the quadcopters maneuver in close proximity resulting in interference due to air-drafts. We use sparse experimental data to estimate the interference area between palm sized quadcopters and to derive physics-infused models that describe how the air-draft generated by two quadcopters (flying one above the other) affect each

This paper proposes an adaptive tracking control scheme for multi-spacecraft formation with inter-collision avoidance, obstacle dodging, and connectivity preservation. The proposed scheme is distributed, i.e., each spacecraft only needs to communicate with its neighbours. Both connectivity preservation and distributed networking are critical features for small spacecraft formation with limited computation

This paper aims to propose a solution to the feasible-trajectory planning problem for a tracked mobile robot subject to non-negligible skidding and slipping effects and whose control system, sensors and actuators are connected through a communication network. A trajectory is defined in terms of succession of linear segments with a prescribed crossing velocity and the trajectory feasibility is guaranteed

Autonomous Mobile Robots (AMRs) have become extremely popular in the manufacturing domain, especially for processes involving large factory floors where these robots are used for transporting materials from one location to another. In an environment where there are multiple prioritized tasks to be completed by a school of AMRs, the overall planning problem can be broken down into three sequential steps:

Cleaning multi-storey buildings need to be considered while developing autonomous service robots. In this paper, we introduce a novel reconfigurable platform called sTetro with the abilitiesto navigate on the floor as well as to detect then climb the staircase autonomously. To this end, an operational framework for this cleaning robot that leverages on customized deep convolution neural network (DCNN)

Autonomous Vehicles have the potential to change the urban transport scenario. However, to be able to safely navigate autonomously they need to deal with faults that its components are subject to. Therefore, Health Monitoring System is a essential component of the autonomous system, since allows Fault Detection and Diagnosis. In addition, Prognosis System is also important, since it allows predictive

We present an algorithmic approach to task deconfliction for teams of autonomous agents in communication-limited environments when the teams produce schedules with strong cross-schedule dependencies without the knowledge of the existence of other teams attempting to prosecute the same task set. Once agents discover others are attempting to prosecute the same task, they deconflict the task by trading

Tracking a visual path to perform image-based control requires additional processing to extract valuable information even in the presence of inconveniences, such as failures or deformation in the lane line or even restrictive environmental conditions. Dealing with faulty in the path to be followed, non-homogeneous floors and bad lighting condition are some of the difficulties encountered that compromise

In this work, we aim to develop a fast trajectory replanning methodology enabling highly agile aerial vehicles to navigate in cluttered environments. By focusing on reducing complexity and accelerating the replanning problem under strict dynamical constraints, we employ the b-spline theory with local support property for defining the high dimensional agile flight trajectories. We utilize the differential

The problem of dynamic behavior control for human-robot collaborative system is studied in this paper. A general dynamic behavior control framework is presented, based on which the interaction control strategies for single-point human-robot collaboration and multi-point human-robot interaction are studied. Through typical human-robot collaborative operation scenarios, the causes of role conflicts under

The main goal of this paper is to address the problem of deploying a team of heterogeneous, autonomous robots in a partially known environment. To handle such arbitrary environments, we first represent them as a weighted directed graph. Then, a new partitioning algorithm is given that is capable of capturing the heterogeneity of robots in terms of the speed and onboard power. It is shown that the proposed

Visual object tracking remains a challenging computer vision problem with numerous real-world applications. Discriminative correlation filter (DCF)-based methods are a recent state-of-the-art approach for dealing with this problem. The learning rate when applying a DCF is typically fixed, regardless of the situation. However, this rate is important for robust tracking, insofar as real-world video sequences

Underwater tank cleaning using robotic method is very crucial due to the concern on the diver’s safety in undisrupted water supply operation. A Remotely Operated Underwater Vehicles (ROV) used in the tank cleaning operation however, suffers from a high operational cost due to the lack of systematic operator guidance in robot maneuvering. This paper presents a multi-objective approach in designing a

Telerobotic system is a typical human-machine system. The operation results not only depend on the performance of machine, but also the status of teleoperators (SoT). However, existing telerobotic systems scarcely consider the impact of teleoperators. This paper proposes a method for the online identification of the SoT and incorporates it to a shared control telerobotic system. First, some mental

A control solution for an Unmanned Aerial Vehicle encapsulating a nonlinear inner-loop based on the application of feedback linearization to the attitude and altitude dynamics is proposed in this paper. Linear quadratic controllers with integrative action are implemented not only to the resulting inner-loop chain of integrators, but also to the outer-loop, that controls the horizontal movement and

The purpose of this paper is to provide details on the implementation of an accurate and intelligent automation solution to achieve the abdomen cutting operation of the porcine carcass. The system consists of an industrial robot, a binocular camera, an end effector, and an industrial computer. Threshold segmentation is used to detect the contour of the porcine carcass. Based on the contour, the kernel

Roadmap is important in typical robotic applications and it is not a trivial task to obtain in unknown space. In this paper, we propose a novel approach to calculate the roadmap that is robust against noisy environmental contours and the movement of the robot. In order to obtain full visibility to space, we design a direct space partitioning approach to produce the roadmap. It uses readings from rangefinders

In recent years, Unmanned Aerial Vehicles (UAVs) are widely utilized in precision agriculture, such as tree plantations. Due to limited intelligence, these UAVs can only operate at high altitudes, leading to the use of expensive and heavy sensors for obtaining important health information of the plants. To fly at low altitudes, these UAVs must possess the capability of obstacle avoidance to prevent

Kinematic calibration of robots is an effective way to guarantee and promote their performance characteristics. There are many mature researches on kinematic calibration, and methods based on MDH model are the most common ones. However, when employing these calibration methods, it occasionally happens that the objective function cannot converge during iterations. Through analyzing robotic forward kinematics

The paper proposes a light-weighted stereo frustums matching module for 3D objection detection. The proposed framework takes advantage of a high-performance 2D detector and a point cloud segmentation network to regress 3D bounding boxes for autonomous driving vehicles. Instead of performing traditional stereo matching to compute disparities, the module directly takes the 2D proposals from both the

This paper presents an incremental learning method and system for autonomous robot navigation. The range finder laser sensor and online deep reinforcement learning are utilized for generating the navigation policy, which is effective for avoiding obstacles along the robot’s trajectories as well as for robot’s reaching the destination. An empirical experiment is conducted under simulation and real-world

Focusing on the problems of big overshoot and long convergence time due to the large initial heading error, a new path tracking control strategy for autonomous harvesting robots based on improved double arc path planning is designed. Firstly, the improved double arc path planning algorithm includes global path planning and local planning. The shortest path distance is taken as the goal, so the optimal

Control theory applied to multirotor aerial systems (MAS) has gained attention with the recent increase on the power computation for embedded systems. These systems are now able to perform the calculations needed for a variety of control techniques, with lower cost of sensors and actuators. These types of control algorithms are applied to the position and the attitude of MAS. In this paper, a brief

In this article, we develop a novel strategy for automatic error classification and recovery in robotic assembly tasks. The strategy does not require error diagnosis. It allows for effective reduction of an undetermined number of error states to 4, without the need for further operator updates of error space. The strategy integrates existing methods for computer vision, active vision and active manipulation

This paper studies the problems of static coverage and autonomous exploration of unknown three-dimensional environments with a team of cooperating aerial vehicles. Although these tasks are usually considered separately in the literature, we propose a common framework where both problems are formulated as the maximization of online acquired information via the definition of single-robot optimization

The development of flexible swarm robotics systems capable of adapting to the task and environmental changes is a serious challenge. The main motivations of Swarm robotics are decentralized control, stability, adaptivity, and flexibility. Usually, ad-hoc approaches are employed to design a controller capable of meeting the problem specifications. However, these methods cannot be easily verified, and

Due to oversight, an incorrect figure in Ref. [1] was printed for Fig. 17. but the original wording and description of Fig. 17 is correct.

In this paper, a RISE (Robust Integral of the Sign Error) controller with adaptive feedforward compensation terms based on Associative Memory Neural Network (AMNN) type B-Spline is proposed to regulate the positioning of a Delta Parallel Robot (DPR) with three degrees of freedom. Parallel Kinematic Manipulators (PKMs) are highly nonlinear systems, so the design of a suitable control scheme represents

Small multi-rotor unmanned aerial vehicles (UAVs) are poised to revolutionize commercial and logistics sectors through their versatility, maneuverability, and rapidly increasing sophistication and decreasing costs. However, these robotic systems also produce a substantial and overpowering level of acoustic noise that can potentially distract or harm humans who are working in close proximity to these

To achieve a manipulator that is lighter and more anthropomorphic, a 7-DOF robotic manipulator driven by the tendon-sheath is designed. Its mechanical system and control system are both introduced in this paper. An encoder is installed on both the driver side and the joint side to realize double closed-loop control. Considering the transmission characteristics of the reducer and the tendon-sheath,

We encounter a world where the role of robots has increased in society. Day by day, we can observe that problems related to autonomous vehicles are being solved. The focused problem that we have recently confronted is based on collaborative mapping with multi-robots since collaboratively generated map provides more information about the environment than with a single robot. Moreover, the mapping framework

This work proposes a novel motion guided method for targetless self-calibration of a LiDAR and camera and use the re-projection of LiDAR points onto the image reference frame for real-time depth upsampling. The calibration parameters are estimated by optimizing an objective function that penalizes distances between 2D and re-projected 3D motion vectors obtained from time-synchronized image and point

Path planning of autonomous mobile robots in a real-world environment presents several challenges which are usually not raised in other areas. The real world is inherently complex, uncertain and dynamic. Therefore, accurate models of path planning are difficult to obtain and quickly become outdated. Anytime planners are ideal for this type of problem as they can find an initial solution very quickly

The intelligent drone is the key device of the future Internet of Drone, and its safe and robust flight in complicated environments still faces challenges. In this paper, we present a sampling-based kinodynamic planning algorithm for quadrotors, which plans a dynamically feasible trajectory in a complicated environment. We have designed a method to constrain the sampling state by using the vector field

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