Towards Complex Human Robot Cooperation Based on Gesture-Controlled Autonomous Navigation

This paper presents a new approach for human robot co- operation, where a mobile ground robot is provided with the ability of following a person that has been detected with a Kinect sensor. It can plan a trajectory to follow the person and avoid obstacles that appear in the environment in an autonomous way. It has been developed to work in coordinated tasks where the person needs to exchange data and ta ke advantage of the sensors, communications and other capabilities of the robot, in order to accomplish a collaborative labor with a situation of proximate interaction. The UGV is controlled by reading some pre defined gestures of the person, and the autonomous navigation is based on a well established navigation scheme. A set of initial experiments demonstrate the feasibility of the system

VSLAM and Navigation System of Unmanned Ground Vehicle Based on RGB-D Camera

In this thesis, ROS (Robot Operating System) is used as the software platform and a simple unmanned ground vehicle that is designed and constructed by myself is used as the hardware platform. The most critical issues in the navigation technology of unmanned ground vehicles in unknown environments -SLAM (Simultaneous Localization and Mapping) and autonomous navigation technology are studied. Through the analysis of the principle and structure of visual SLAM, a visual simultaneous localization and mapping algorithm is build. Moreover, accelerate the visual SLAM algorithm through hardware replacement and software algorithm optimization. RealSense D435 is used as the camera of the VSLAM sensor. The algorithm extracts the features from the data of depth camera and calculates the odometry information of the unmanned vehicle through the features matching of the adjacent image. Then update the vehicle’s location and map data using the odometry information. Under the condition that the visual SLAM algorithm works normally, this thesis also uses the 3D map generated to derive the real-time 2D projection map. So as to apply it to the navigation algorithm. Then this thesis realize autonomous navigation and avoids the obstacle function of unmanned vehicle by controlling the driving speed and direction of the vehicle through the navigation algorithm using the 2D projection map. Unmanned ground vehicle path planning is mainly two parts: local path planning and global path planning. Global path planning is mainly used to plan the optimal path to the destination. Local path planning is mainly used to control the speed and direction of the UGV. This thesis analyzes and compares Dijkstra’s algorithm and A* algorithm. Considering the compatible to ROS, Dijkstra’s algorithm is finally used as the global path-planning algorithm. DWA (Dynamic Window Approach) algorithm is used as Local path planning. Under the control of the Dijkstra’s algorithm and the DWA algorithm, unmanned ground vehicles can automatically plan the optimal path to the target point and avoid obstacles. This thesis also designed and constructed a simple unmanned ground vehicle as an experimental platform and design a simple control method basing on differential wheeled unmanned ground vehicle and finally realized the autonomous navigation of unmanned ground vehicles and the function of avoiding obstacles through visual SLAM algorithm and autonomous navigation algorithm. Finally, the main work and deficiencies of this thesis are summarized. And the prospects and difficulties of the research field of unmanned ground vehicles are presented

Unmanned Ground Robots for Rescue Tasks

This chapter describes two unmanned ground vehicles that can help search and rescue teams in their difficult, but life-saving tasks. These robotic assets have been developed within the framework of the European project ICARUS. The large unmanned ground vehicle is intended to be a mobile base station. It is equipped with a powerful manipulator arm and can be used for debris removal, shoring operations, and remote structural operations (cutting, welding, hammering, etc.) on very rough terrain. The smaller unmanned ground vehicle is also equipped with an array of sensors, enabling it to search for victims inside semi-destroyed buildings. Working together with each other and the human search and rescue workers, these robotic assets form a powerful team, increasing the effectiveness of search and rescue operations, as proven by operational validation tests in collaboration with end users

Cooperative UAV–UGV autonomous power pylon inspection: an investigation of cooperative outdoor vehicle positioning architecture

Realizing autonomous inspection, such as that of power distribution lines, through unmanned aerial vehicle (UAV) systems is a key research domain in robotics. In particular, the use of autonomous and semi-autonomous vehicles to execute the tasks of an inspection process can enhance the efficacy and safety of the operation; however, many technical problems, such as those pertaining to the precise positioning and path following of the vehicles, robust obstacle detection, and intelligent control, must be addressed. In this study, an innovative architecture involving an unmanned aircraft vehicle (UAV) and an unmanned ground vehicle (UGV) was examined for detailed inspections of power lines. In the proposed strategy, each vehicle provides its position information to the other, which ensures a safe inspection process. The results of real-world experiments indicate a satisfactory performance, thereby demonstrating the feasibility of the proposed approach.This research was funded by National Counsel of Technological and Scientific Development of Brazil (CNPq). The authors thank the National Counsel of Technological and Scientific Development of Brazil (CNPq); Coordination for the Improvement of Higher Level People (CAPES); and the Brazilian Ministry of Science, Technology, Innovation, and Communication (MCTIC). The authors would also like express their deepest gratitude to Control Robotics for sharing the Pioneer P3 robot for the experiments. Thanks to Leticia Cantieri for editing the experiment video.info:eu-repo/semantics/publishedVersio

Robotic navigation in the presence of static and dynamic obstacles

Computer Vision is the analytic study of motion dependent machines that extract valuable information from an image and perform some algorithmic processing on the captured images to derive necessary information to solve a particular or a set of tasks. Computer vision is the reconstruction of explicit, meaningful descriptions of physical objects obtained from their images. As far as scientific discipline is concerned, it moreover concerns itself with the theoretical aspects related to artificial intelligent systems that extract valuable information from the captured images. The role of computer vision in automated system is providing the detailed information about the working environment. A robust vision system should always be able to detect as well as identify objects reliably and provide an accurate and precise information as well as representation of the environment conditions to high level processes. The robust vision system should be highly effective and efficient, allowing all the objects which are limited and used as resource to respond quickly to a changing environment. Computer Vision is the key aspect to the design of the automatic responsive system by virtue of which the objects in the system localize themselves in the environment and act according to the changing nature of the environment variables. The objective of the project was to build an autonomous vehicle for urban road which could guide itself to the specified location based on its decision making quality on basis of the path analysis using image processing and GPS. It would guide from the present source to the destination based on the path created using the wave points with obstacle avoidance of all objects, both static and dynamic in nature. It should also be capable of switching into manual mode control upon instruction being issued i.e. it can be controlled manually using the manual wireless control using X-Bee wireless module

Investigation into the effects of transmission-channel fidelity loss in RGBD sensor data for SLAM

Simultaneous Location and Mapping (SLAM) is computationally expensive, and requires high-fidelity sensor data. This paper investigates the effects of transmission channel fidelity loss in Red-Green-Blue-Depth (RGBD) sensor data. A mobile robotic platform developed for Explosive Ordinance Disposal (EOD) is used, with a highly constrained data and video link to a base station which computes a SLAM solution. Experiments were conducted offline, using well known data-sets with ground truth data, and their results have been compared to determine the effect of fidelity loss under various multiplexing approaches with a constrained transmission channel

Coordinated Landing and Mapping with Aerial and Ground Vehicle Teams

Micro Umanned Aerial Vehicle~(UAV) and Umanned Ground Vehicle~(UGV) teams present tremendous opportunities in expanding the range of operations for these vehicles. An effective coordination of these vehicles can take advantage of the strengths of both, while mediate each other's weaknesses. In particular, a micro UAV typically has limited flight time due to its weak payload capacity. To take advantage of the mobility and sensor coverage of a micro UAV in long range, long duration surveillance mission, a UGV can act as a mobile station for recharging or battery swap, and the ability to perform autonomous docking is a prerequisite for such operations. This work presents an approach to coordinate an autonomous docking between a quadrotor UAV and a skid-steered UGV. A joint controller is designed to eliminate the relative position error between the vehicles. The controller is validated in simulations and successful landing is achieved in indoor environment, as well as outdoor settings with standard sensors and real disturbances. Another goal for this work is to improve the autonomy of UAV-UGV teams in positioning denied environments, a very common scenarios for many robotics applications. In such environments, Simultaneous Mapping and Localization~(SLAM) capability is the foundation for all autonomous operations. A successful SLAM algorithm generates maps for path planning and object recognition, while providing localization information for position tracking. This work proposes an SLAM algorithm that is capable of generating high fidelity surface model of the surrounding, while accurately estimating the camera pose in real-time. This algorithm improves on a clear deficiency of its predecessor in its ability to perform dense reconstruction without strict volume limitation, enabling practical deployment of this algorithm on robotic systems

Localization And Mapping Of Unknown Locations And Tunnels With Unmanned Ground Vehicles

The main goals of this research were to enhance a commercial off the shelf (COTS) software platform to support unmanned ground vehicles (UGVs) exploring the complex environment of tunnels, to test the platform within a simulation environment, and to validate the architecture through field testing. Developing this platform will enhance the U. S. Army Engineering Research and Development Center’s (ERDC’s) current capabilities and create a safe and efficient autonomous vehicle to perform the following functions within tunnels: (1) localization (e.g., position tracking) and mapping of its environment, (2) traversing varied terrains, (3) sensing the environment for objects of interest, and (4) increasing the level of autonomy of UGVs available at the ERDC. The simulation experiments were performed in the STAGE Simulator, a physics-based multi-scale numerical test bed developed by Robotic Operating System (ROS). Physical testing was conducted in Vicksburg, MS using a Coroware Explorer. Both the simulation and physical testing evaluated three SLAM algorithms, i.e., Hector SLAM, gMapping, and CORESLAM to determine the superior algorithm. The superior algorithm was then used to localize the robot to the environment and autonomously travel from a start location to a destination location. Completion of this research has increased the ERDC’s level of autonomy for UGVs from tether to tele-operated to autonomous

Deployable Vibration Control Systems for Lightweight Structures

The recent push towards lightweight, efficient, and innovative structural designs has brought forth a range of vibration control issues related to implementation, effectiveness, and control system design that are not fully addressed by existing strategies. In many cases, these structures are capable of withstanding day-to-day loads and only experience excessive vibrations during predictable peak-loading events such as large crowds or wind storms. At the same time, the use of lightweight material coupled with innovative construction methods has given rise to temporary structures which are designed to facilitate rapid implementation and intended for short-term applications. Both scenarios point towards a vibration control system that is suitable for immediate, short-term applications which motivates the concept of deployable autonomous control systems (DACSs). The deployability aspect implies the control system is capable of being readily implemented on a range of structures with only minor customization to the structure or device while the autonomy aspect refers to the ability of the system to react to changes in the dynamic response and effectively control different structural modes of vibration. A prototype device, consisting of an electromagnetic mass damper (EMD) mounted on an unmanned ground vehicle (UGV) equipped with vision sensors and on-board computational hardware, is developed to study the vibration control performance and demonstrate the advantages of the DACS concept. Both numerical and experimental modelling techniques are used to identify system models for each component of the prototype device. Given the system models, the dynamic interaction between the device and underlying structure is derived theoretically and validated experimentally. The use of an EMD and UGV introduce a number of practical challenges associated with controller design. These challenges arise due to the presence of physical operating constraints as well as uncertainty in the controller model. Three different candidate controllers, based on linear-quadratic Gaussian (LQG), model-predictive control (MPC), and robust H-infinity control theory, are formulated for the prototype device and comparatively assessed with respect to their ability to address these challenges. The MPC framework provides a systematic approach to incorporate physical operating constraints directly in the control formulation while robust synthesis of an H-infinity controller is well suited for addressing uncertainty in both the controller and structure models. A key property of the prototype device is the ability to reposition itself at different locations on the structure. To study the impact of this mobility on the overall control performance, a simultaneous localization and mapping (SLAM) solution is implemented for bridge structures. The SLAM solution generates a map of the structure that can later be used for autonomous navigation of the prototype device. In achieving autonomous mobility, the location of the control force can be added as an additional parameter in the controller formulation. The overall performance of the prototype device is evaluated through a combination of numerical simulations and experimental studies. Real-time hybrid simulation (RTHS) is used extensively to study the dynamic interaction effects and evaluate the control performance of the prototype device on various structures. A full-scale modular aluminum pedestrian bridge is used to demonstrate autonomous navigation and assess the advantages of a mobile control device. The results from each study point towards DACSs as being a favourable alternative to existing control systems for immediate, short-term vibration control applications