Intelligent Navigation Service Robot Working in a Flexible and Dynamic Environment

Numerous sensor fusion techniques have been reported in the literature for a number of robotics applications. These techniques involved the use of different sensors in different configurations. However, in the case of food driving, the possibility of the implementation has been overlooked. In restaurants and food delivery spots, enhancing the food transfer to the correct table is neatly required, without running into other robots or diners or toppling over. In this project, a particular algorithm module has been proposed and implemented to enhance the robot driving methodology and maximize robot functionality, accuracy, and the food transfer experience. The emphasis has been on enhancing movement accuracy to reach the targeted table from the start to the end. Four major elements have been designed to complete this project, including mechanical, electrical, electronics, and programming. Since the floor condition greatly affecting the wheels and turning angle selection, the movement accuracy was improved during the project. The robot was successfully able to receive the command from the restaurant and go to deliver the food to the customers\u27 tables, considering any obstacles on the way to avoid. The robot has equipped with two trays to mount the food with well-configured voices to welcome and greet the customer. The performance has been evaluated and undertaken using a routine robot movement tests. As part of this study, the designed service wheeled robot required to be with a high-performance real-time processor. As long as the processor was adequate, the experimental results showed a highly effective search robot methodology. Having concluded from the study that a minimum number of sensors are needed if they are placed appropriately and used effectively on a robot\u27s body, as navigation could be performed by using a small set of sensors. The Arduino Due has been used to provide a real-time operating system. It has provided a very successful data processing and transfer throughout any regular operation. Furthermore, an easy-to-use application has been developed to improve the user experience, so that the operator can interact directly with the robot via a special setting screen. It is possible, using this feature, to modify advanced settings such as voice commands or IP address without having to return back to the code

Path planning algorithms for autonomous navigation of a non-holonomic robot in unstructured environments

openPath planning is a crucial aspect of autonomous robot navigation, enabling robots to efficiently and safely navigate through complex environments. This thesis focuses on autonomous navigation for robots in dynamic and uncertain environments. In particular, the project aims to analyze the localization and path planning problems. A fundamental review of the existing literature on path planning algorithms has been carried on. Various factors affecting path planning, such as sensor data fusion, map representation, and motion constraints, are also analyzed. Thanks to the collaboration with E80 Group S.p.A., the project has been developed using ROS (Robot Operating System) on a Clearpath Dingo-O, an indoor mobile robot. To address the challenges posed by unstructured and dynamic environments, ROS follows a combined approach of using a global planner and a local planner. The global planner generates a high-level path, considering the overall environment, while the local planner handles real-time adjustments to avoid moving obstacles and optimize the trajectory. This thesis describes the role of the global planner in a ROS-framework. Performance benchmarking of traditional algorithms like Dijkstra and A*, as well as other techniques, is fundamental in order to understand the limits of these methods. In the end, the Hybrid A* algorithm is introduced as a promising approach for addressing the issues of unstructured environments for autonomous navigation of a non-holonomic robot. The core concepts and implementation details of the algorithm are discussed, emphasizing its ability to efficiently explore continuous state spaces and generate drivable paths.The effectiveness of the proposed path planning algorithms is evaluated through extensive simulations and real-world experiments using the mobile platform. Performance metrics such as path length, execution time, and collision avoidance are analyzed to assess the efficiency and reliability of the algorithms.Path planning is a crucial aspect of autonomous robot navigation, enabling robots to efficiently and safely navigate through complex environments. This thesis focuses on autonomous navigation for robots in dynamic and uncertain environments. In particular, the project aims to analyze the localization and path planning problems. A fundamental review of the existing literature on path planning algorithms has been carried on. Various factors affecting path planning, such as sensor data fusion, map representation, and motion constraints, are also analyzed. Thanks to the collaboration with E80 Group S.p.A., the project has been developed using ROS (Robot Operating System) on a Clearpath Dingo-O, an indoor mobile robot. To address the challenges posed by unstructured and dynamic environments, ROS follows a combined approach of using a global planner and a local planner. The global planner generates a high-level path, considering the overall environment, while the local planner handles real-time adjustments to avoid moving obstacles and optimize the trajectory. This thesis describes the role of the global planner in a ROS-framework. Performance benchmarking of traditional algorithms like Dijkstra and A*, as well as other techniques, is fundamental in order to understand the limits of these methods. In the end, the Hybrid A* algorithm is introduced as a promising approach for addressing the issues of unstructured environments for autonomous navigation of a non-holonomic robot. The core concepts and implementation details of the algorithm are discussed, emphasizing its ability to efficiently explore continuous state spaces and generate drivable paths.The effectiveness of the proposed path planning algorithms is evaluated through extensive simulations and real-world experiments using the mobile platform. Performance metrics such as path length, execution time, and collision avoidance are analyzed to assess the efficiency and reliability of the algorithms

Design and Development of an Inspection Robotic System for Indoor Applications

The inspection and monitoring of industrial sites, structures, and infrastructure are important issues for their sustainability and further maintenance. Although these tasks are repetitive and time consuming, and some of these environments may be characterized by dust, humidity, or absence of natural light, classical approach relies on large human activities. Automatic or robotic solutions can be considered useful tools for inspection because they can be effective in exploring dangerous or inaccessible sites, at relatively low-cost and reducing the time required for the relief. The development of a paradigmatic system called Inspection Robotic System (IRS) is the main objective of this paper to demonstrate the feasibility of mechatronic solutions for inspection of industrial sites. The development of such systems will be exploited in the form of a tool kit to be flexible and installed on a mobile system, in order to be used for inspection and monitoring, possibly introducing high efficiency, quality and repetitiveness in the related sector. The interoperability of sensors with wireless communication may form a smart sensors tool kit and a smart sensor network with powerful functions to be effectively used for inspection purposes. Moreover, it may constitute a solution for a broad range of scenarios spacing from industrial sites, brownfields, historical sites or sites dangerous or difficult to access by operators. First experimental tests are reported to show the engineering feasibility of the system and interoperability of the mobile hybrid robot equipped with sensors that allow real-time multiple acquisition and storage

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover mothership. Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a local GPS) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed

Automation and robotics for the Space Exploration Initiative: Results from Project Outreach

A total of 52 submissions were received in the Automation and Robotics (A&R) area during Project Outreach. About half of the submissions (24) contained concepts that were judged to have high utility for the Space Exploration Initiative (SEI) and were analyzed further by the robotics panel. These 24 submissions are analyzed here. Three types of robots were proposed in the high scoring submissions: structured task robots (STRs), teleoperated robots (TORs), and surface exploration robots. Several advanced TOR control interface technologies were proposed in the submissions. Many A&R concepts or potential standards were presented or alluded to by the submitters, but few specific technologies or systems were suggested

An Approach for Multi-Robot Opportunistic Coexistence in Shared Space

This thesis considers a situation in which multiple robots operate in the same environment towards the achievement of different tasks. In this situation, please consider that not only the tasks, but also the robots themselves are likely be heterogeneous, i.e., different from each other in their morphology, dynamics, sensors, capabilities, etc. As an example, think about a "smart hotel": small wheeled robots are likely to be devoted to cleaning floors, whereas a humanoid robot may be devoted to social interaction, e.g., welcoming guests and providing relevant information to them upon request. Under these conditions, robots are required not only to co-exist, but also to coordinate their activity if we want them to exhibit a coherent and effective behavior: this may range from mutual avoidance to avoid collisions, to a more explicit coordinated behavior, e.g., task assignment or cooperative localization. The issues above have been deeply investigated in the Literature. Among the topics that may play a crucial role to design a successful system, this thesis focuses on the following ones: (i) An integrated approach for path following and obstacle avoidance is applied to unicycle type robots, by extending an existing algorithm [1] initially developed for the single robot case to the multi-robot domain. The approach is based on the definition of the path to be followed as a curve f (x;y) in space, while obstacles are modeled as Gaussian functions that modify the original function, generating a resulting safe path. The attractiveness of this methodology which makes it look very simple, is that it neither requires the computation of a projection of the robot position on the path, nor does it need to consider a moving virtual target to be tracked. The performance of the proposed approach is analyzed by means of a series of experiments performed in dynamic environments with unicycle-type robots by integrating and determining the position of robot using odometry and in Motion capturing environment. (ii) We investigate the problem of multi-robot cooperative localization in dynamic environments. Specifically, we propose an approach where wheeled robots are localized using the monocular camera embedded in the head of a Pepper humanoid robot, to the end of minimizing deviations from their paths and avoiding each other during navigation tasks. Indeed, position estimation requires obtaining a linear relationship between points in the image and points in the world frame: to this end, an Inverse Perspective mapping (IPM) approach has been adopted to transform the acquired image into a bird eye view of the environment. The scenario is made more complex by the fact that Pepper\u2019s head is moving dynamically while tracking the wheeled robots, which requires to consider a different IPM transformation matrix whenever the attitude (Pitch and Yaw) of the camera changes. Finally, the IPM position estimate returned by Pepper is merged with the estimate returned by the odometry of the wheeled robots through an Extened Kalman Filter. Experiments are shown with multiple robots moving along different paths in a shared space, by avoiding each other without onboard sensors, i.e., by relying only on mutual positioning information. Software for implementing the theoretical models described above have been developed in ROS, and validated by performing real experiments with two types of robots, namely: (i) a unicycle wheeled Roomba robot(commercially available all over the world), (ii) Pepper Humanoid robot (commercially available in Japan and B2B model in Europe)

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings