Fleet Of Robots Research Articles

Cross-Flaming Application for Intra-Row Weed Control in Maize

Abstract. Flame weeding is the most common thermal intra-row weed control method used in agriculture as an alternative to herbicides in heat-tolerant crops. Within the seventh framework program project “Robot fleets for Highly Effective Agriculture and Forestry Management” (RHEA), the University of Pisa was responsible for the development of an automatic machine for intra-row cross-flaming in maize ( L.). This study focused on the selection of a range of liquid petroleum gas (LPG) doses able to control weeds without affecting crop yields, for the basic calibration of the machine. Tests were conducted in 2012 and 2013 during the growing cycle of maize both in weed-free and real-field weedy conditions. Five biological LPG doses (0, 52, 65, 104, and 130 kg ha-1) were applied at different maize growth stages once (2- and 5-leaf) and twice (2-leaf the first time and 16 days after the first time). The response of maize and weeds to cross-flaming was evaluated in terms of grain yield, weed density after flame weeding, and weed dry biomass at harvest. Log-logistic models were used to describe the responses of different growth stages of maize and weeds to single and repeated applications of LPG doses. Overall response of maize yield to flame weeding was influenced by LPG dose, number of flame weedings, maize growth stage, and presence of weeds. The results of this study indicate that two cross-flaming treatments applied separately with an LPG dose ranging from 36 to 42 kg ha-1 can provide an acceptable level of weed control in maize, enough to ensure economically acceptable yields.

Fleets of robots for environmentally-safe pest control in agriculture

Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.

Sensor Localization from Distance and Orientation Constraints.

The sensor localization problem can be formalized using distance and orientation constraints, typically in 3D. Local methods can be used to refine an initial location estimation, but in many cases such estimation is not available and a method able to determine all the feasible solutions from scratch is necessary. Unfortunately, existing methods able to find all the solutions in distance space can not take into account orientations, or they can only deal with one- or two-dimensional problems and their extension to 3D is troublesome. This paper presents a method that addresses these issues. The proposed approach iteratively projects the problem to decrease its dimension, then reduces the ranges of the variable distances, and back-projects the result to the original dimension, to obtain a tighter approximation of the feasible sensor locations. This paper extends previous works introducing accurate range reduction procedures which effectively integrate the orientation constraints. The mutual localization of a fleet of robots carrying sensors and the position analysis of a sensor moved by a parallel manipulator are used to validate the approach.

Online human assisted and cooperative pose estimation of 2D cameras

Autonomous robots performing cooperative tasks need to know the relative pose of the other robots in the fleet. Deducing these poses might be performed through structure from motion methods in the applications where there are no landmarks or GPS, for instance, in non-explored indoor environments. Structure from motion is a technique that deduces the pose of cameras only given only the 2D images. This technique relies on a first step that obtains a correspondence between salient points of images. For this reason, the weakness of this method is that poses cannot be estimated if a proper correspondence is not obtained due to low quality of the images or images that do not share enough salient points. We propose, for the first time, an interactive structure-from-motion method to deduce the pose of 2D cameras. Autonomous robots with embedded cameras have to stop when they cannot deduce their position because the structure-from-motion method fails. In these cases, a human interacts by simply mapping a pair of points in the robots’ images. Performing this action the human imposes the correct correspondence between them. Then, the interactive structure from motion is capable of deducing the robots’ lost positions and the fleet of robots can continue their high level task. From the practical point of view, the interactive method allows the whole system to achieve more complex tasks in more complex environments since the human interaction can be seen as a recovering or a reset process.

Robotics In Agriculture

Computer-based sensors and actuators such as worldwide positioning systems, appliance vision, and laser-based sensors have increasingly been incorporated into mobile robots with the aim of configuring independent systems capable of shifting operator activities in agricultural tasks. However, the incorporation of many electronic systems into a robot impairs its trustworthiness and increases its cost. Hardware minimization, as well as software minimization and ease of combination, is essential to obtain feasible robotic systems. A step forward in the application of mechanical equipment in agriculture is the use of fleets of robots, in which a number of expert robots collaborate to accomplish one or several rural tasks.

Autonomous systems for precise spraying – Evaluation of a robotised patch sprayer

Advances in different technologies, such as global navigation satellite systems, geographic information systems, high-resolution vision systems, innovative sensors and embedded computing systems, are finding direct application in agriculture. These advances allow researchers and engineers to automate and robotise agricultural tasks no matter the inherent difficulties of the natural, semi-structured environment in which these tasks are performed. Following this current trend, this article aims to describe the development and assessment of a robotised patch spraty -20ying system that was devised for site-specific herbicide application in agricultural crops and is capable of working in groups or fleets of autonomous robots. The robotised patch sprayer consisted of an autonomous mobile robot based on a commercial agricultural vehicle chassis and a direct-injection spraying boom that was tailor-made to interact with the mobile robot. There were diverse sources (on-board and remote sensors) that can supply the weed data for the treatment. The main features of both the mobile robot and the sprayer are presented along with the controller that harmonised the behaviour of both main subsystems. Laboratory characterisation and field tests demonstrated that the system was reliable and accurate enough to accomplish the treatment over 99.5% of the detected weeds and treatment of the crop with no weed treated was insignificant; approximately 0.5% with respect to the total weed patches area, achieving a significant herbicide savings.

On-line compositional controller synthesis for AGV

This paper deals with the on-line design of a supervisor to coordinate an automated guided vehicle (AGV) fleet. This supervisor ensures the system safety (no collision) and a good coordination between vehicles (no blocking situations). It is the so-called Wonham-Ramadge supervisor, it is the least restrictive, and ensures controllability and nonblocking. We propose a compositional procedure to resolve this problem allowing an efficient on-line synthesis. A calculation on the fly is made at every attribution of a new mission for an AGV, to actualize the supervisor and adapt it to the new situation. This compositional approach allows to increase the number of AGV taken on compared to the monolithic approach. We show on some tests the efficiency of this method for the on-line synthesis of supervisor to coordinate a fleet of mobile robots for real cases.

A Multirobot System for Distributed Area Coverage and Signal Searching in Large Outdoor Scenarios*

This work presents a complete multirobot solution for signal searching tasks in large outdoor scenarios. An evaluation of two different coverage path-planning strategies according to field size and shape is presented. A signal location system developed to simulate mines or chemical source detections is also described. The solution presented is a pioneer in evaluating multimaster robotics operative system architectures with a fleet of robots in real scenarios. This solution minimizes the use of communications bandwidth required for full operation. Finally, field results are provided, and the advantages of the implemented solution are analyzed.

Cooperative pose estimation of a fleet of robots based on interactive points alignment

Given a fleet of autonomous robots performing a cooperative task, such as rescue of people, it is crucial for the robots to share their relative position. If the site has not been explored before, auto localise each robot through landmarks is not possible. Moreover, not always the GPS information is available or it has the desirable accuracy. Our framework is composed of a fleet of robots that have 2D and 3D cameras, a human coordinator and a Human–Machine Interface. 3D-images are used to automatically align them and deduct the relative position between robots. 2D-images are used to reduce the alignment error in an interactive manner. A human visualises both 2D-images and the current automatic alignment and imposes a new alignment through the Human–Machine Interface. Since the information is shared through the whole fleet, robots can deduct the position of other ones that do not visualise the same scene. Practical evaluation shows that in situations that there is a large difference between images, the cooperative and interactive processes are crucial to achieve an acceptable result.

UAV-BASED ACQUISITION OF 3D POINT CLOUD – A COMPARISON OF A LOW-COST LASER SCANNER AND SFM-TOOLS

Abstract. The Project ADFEX (Adaptive Federative 3D Exploration of Multi Robot System) pursues the goal to develop a time- and cost-efficient system for exploration and monitoring task of unknown areas or buildings. A fleet of unmanned aerial vehicles equipped with appropriate sensors (laser scanner, RGB camera, near infrared camera, thermal camera) were designed and built. A typical operational scenario may include the exploration of the object or area of investigation by an UAV equipped with a laser scanning range finder to generate a rough point cloud in real time to provide an overview of the object on a ground station as well as an obstacle map. The data about the object enables the path planning for the robot fleet. Subsequently, the object will be captured by a RGB camera mounted on the second flying robot for the generation of a dense and accurate 3D point cloud by using of structure from motion techniques. In addition, the detailed image data serves as basis for a visual damage detection on the investigated building. This paper focuses on our experience with use of a low-cost light-weight Hokuyo laser scanner onboard an UAV. The hardware components for laser scanner based 3D point cloud acquisition are discussed, problems are demonstrated and analyzed, and a quantitative analysis of the accuracy potential is shown as well as in comparison with structure from motion-tools presented.

Automation Highlights from the Literature

Automation Highlights from the Literature

Comparison of Positional Accuracy betweenRTK and RTX GNSS Based on the Autonomous Agricultural Vehicles under Field Conditions

<abstract> <bold><sc>Abstract. </sc></bold>Currently, many systems (machine vision, high resolution remote sensing, global positioning systems, and odometry techniques) have been integrated into agricultural equipment to increase the efficiency, productivity, and safety of the individual in all field activities. This study focused upon assessing a satellite-based localization solution used in straight path guidance of an autonomous vehicle developed for agricultural applications. The autonomous agricultural vehicle was designed and constructed under RHEA (Robot fleets for highly effective agriculture and forestry management) project and is part of a three-unit fleet of similar vehicles. Static tests showed that 99% of all positions are placed within a circle with a 2.9 cm radius centered at the geo-position using real-time satellite corrections (RTX). Dynamic tests between rows demonstrated a mean (N=610) of the standard deviation for real-time base station corrections (RTK) of 1.43 cm and for real-time satellite corrections (RTX) of 2.55 cm. These results demonstrate that the tractor was able to track each straight line with high degree of accuracy. The integration of a Global Navigation Satellite System (GNSS) with sensors (e.g., inertial sensor, altimeters, odometers, etc.) within the vehicle showed the potential of autonomous tractors for expanding agricultural applications utilizing this technology.

An Approach to Distributed Predictive Control for Tracking–Theory and Applications

In this brief paper, a new distributed model predictive control algorithm for the solution of the tracking problem is presented for systems made by a number of dynamically coupled subsystems. The method is developed according to a hierarchical structure, and it guarantees that state and control constraints are fulfilled and that the controlled outputs reach the prescribed reference values whenever possible, or their nearest feasible value when feasibility problems arise. The algorithm is used for control of a small fleet of unicycle robots, and of a simulated four-tank system.

Harnessing coherence of area decomposition and semantic shared spaces for task allocation in a robotic fleet

Task allocation is a fundamental problem in multi-robot systems where heterogeneous robots cooperate to perform a complex mission. A general requirement in a task allocation algorithm is to find an optimal set of robots to execute a certain task. This paper presents the work that harnesses an area decomposition algorithm, and a space-based middleware to facilitate task allocation process in unstructured and dynamic environments. To reduce spatial interference between robots, area decomposition algorithm divides a working area into cells which are then dynamically assigned to robots. In addition, coordination and collaboration among distributed robots are realized through a space-based middleware. For this purpose, the space-based middleware is extended with a semantic model of robot capabilities to improve task selection in terms of flexibility, scalability, and reduced communication overhead during task allocation. In this way a framework which exploits the synergy of area decomposition and semantically enriched space-based approach is created. We conducted performance tests in a specific precision agriculture use case focusing on the utilization of a robotic fleet for weed control introduced in the European Project RHEA – Robot Fleets for Highly Effective Agriculture and Forestry Management.

Adaptable Robot Formation Control: Adaptive and Predictive Formation Control of Autonomous Vehicles

The ability to use cooperative small vehicles is of interest in many applications. From material transportation to farming operations, the use of small machines achieving small tasks, but able to work together to complete larger tasks, permits us to rely on a unique kind of vehicle. To be efficient, such a point of view requires the vehicles to be, at least partially, autonomous and their motion must be accurately coordinated for the tasks to be properly achieved. This article proposes a control framework dedicated to the accurate control of a fleet of mobile robots operating in formation. Decentralized control relying on interrobot communication has been favored. To ensure a high relative positioning, adaptive and predictive control techniques are considered, allowing us to account for the influence of several phenomena (such as dynamic perturbations or bad grip conditions) depreciating the relevance of classical approaches based on ideal robots and ideal contact conditions assumptions.

New Trends in Robotics for Agriculture: Integration and Assessment of a Real Fleet of Robots

Computer-based sensors and actuators such as global positioning systems, machine vision, and laser-based sensors have progressively been incorporated into mobile robots with the aim of configuring autonomous systems capable of shifting operator activities in agricultural tasks. However, the incorporation of many electronic systems into a robot impairs its reliability and increases its cost. Hardware minimization, as well as software minimization and ease of integration, is essential to obtain feasible robotic systems. A step forward in the application of automatic equipment in agriculture is the use of fleets of robots, in which a number of specialized robots collaborate to accomplish one or several agricultural tasks. This paper strives to develop a system architecture for both individual robots and robots working in fleets to improve reliability, decrease complexity and costs, and permit the integration of software from different developers. Several solutions are studied, from a fully distributed to a whole integrated architecture in which a central computer runs all processes. This work also studies diverse topologies for controlling fleets of robots and advances other prospective topologies. The architecture presented in this paper is being successfully applied in the RHEA fleet, which comprises three ground mobile units based on a commercial tractor chassis.

Nonlinear Stability and Boundedness of Approximately Symmetric Large-Scale Systems

Stability and convergence properties of large-scale integrated systems are essential aspects of the development of truly useful and well-designed cyber-physical systems (CPS). Because of the desire for flexible, adaptive and reactive cyber-physical systems, i.e., global operation, nonlinear analyses and tools are especially important in CPS. Hence, Lyapunov methods are at the core of many critical control methodologies for such systems. This paper considers Lyapunov stability for approximately symmetric systems. Many robotic systems, such as swarms and fleets of mobile robots, distributed sensor networks, highly integrated cyber-physical systems, etc., are comprised many identical interacting agents, and our prior work has developed computationally efficient stability analyses of the control and dynamics of such symmetric systems. This paper extends those results to the important case where all the agents are not identical, which is important for real-world applications where it is not possible to have exactly identical agents. Importantly, these results do not require the components to have small differences. However, the bounds on the nature of the solutions will obviously depend on how different the agents are.

Selective Smooth Fictitious Play: An approach based on game theory for patrolling infrastructures with a multi-robot system

The multi-robot patrolling problem is defined as the activity of traversing a given environment. In this activity, a fleet of robots visits some places at irregular intervals of time for security purpose. To date, this problem has been solved with different approaches. However, the approaches that obtain the best results are unfeasible for security applications because they are centralized and deterministic. To overcome the disadvantages of previous work, this paper presents a new distributed and non-deterministic approach based on a model from game theory called Smooth Fictitious Play. To this end, the multi-robot patrolling problem is formulated by using concepts of graph theory to represent an environment. In this formulation, several normal-form games are defined at each node of the graph. This approach is validated by comparison with best suited literature approaches by using a patrolling simulator. The results for the proposed approach turn out to be better than previous literature approaches in as many as 88% of the cases of study. Moreover, the novel approach presented in this work has many advantages over other approaches of the literature such distribution, robustness, scalability, and dynamism. The achievements obtained in this work validate the potential of game theory to protect infrastructures.

The RHEA-project robot for tree crops pesticide application

The sustainable use of pesticide and the need of a renewed integrated system of agricultural knowledge and management, focus the designing of the EU FP7 RHEA Project. The objectives are the design, development, and testing of a new automatic generation of robotic systems to perform field operations for the sustainable crop management. The project affects three case study: chemical, physical, mechanical and thermal effective weed management in maize and wheat cultivations and chemical pesticide management in woody crops. To achieve the goals, a fleet of small and heterogeneous robots, ground and aerial, equipped with advanced sensors, innovative end actuators and decision control algorithms were realized. Present work is related to the third case study considered i.e. the spraying in woody crops specifically in olive trees. The final decision on woody perennial crops treatment device system, was oriented toward a complete double side air blast sprayer with eight separate spraying modules on four vertical bands of the canopy. Rhea air blast sprayer introduces some important innovations in the studies concerning the pesticide variable rate treatment, i.e. the management possibility of air flow in site specific way and in real time in function of the target.

Ocean Space and the Anthropocene, new notions in geosciences? – An essay

AbstractTwo notions, Ocean Space and the Anthropocene, are discussed. The first is occasionally used in legal and governance literature, and in the media. The Anthropocene, however, is widely applied in the global change research community and the media. The notion of ocean space stands for a holistic, system science approach combined with 4D thinking from the ocean, and the processes within it, towards the land. Ocean space is in fact a social-ecological concept that deals with sustainability challenges which are the consequence of the complex interactions between humans and the marine environment on all scales. Ocean space is, on a human scale, impressively large. On a planetary scale, however, it is insignificant, although it has been an ancient feature of the Earth for the last four billion years or so. Yet, ocean space is a critical player in the Earth System; it is central to climate regulation, the hydrological and carbon cycles and nutrient flows, it balances levels of atmospheric gases, it is a source of raw materials vital for medical and other uses, and a sink for anthropogenic pollutants. The notion also encompasses issues such as exploration, adventure, science, resources, conservation, sustainability, etc., and should be an innovative and attractive outreach instrument for the media. Finally, it marks the fundamental change in ocean exploration in the twenty-first century in which ocean-observing systems, and fleets of robots, are routinely and continuously providing quality controlled data and information on the present and future states of ocean space. Advocates of the notion of the Anthropocene argue that this new epoch in geological time, commenced with the British industrial revolution. To date, the Anthropocene has already been subdivided into three stages. The first of these coincides with the beginning of the British industrial revolution around 1800. This transition quickly transformed a society which used natural energy sources into one that uses fossil fuels. The present high-energy society of more than seven billion people mostly with highly improved living standards and birth rates, and a global economy, is the consequence. The downside of this development comprises intensive resource and land use as well as large-scale pollution of the (marine) environment. The first stage of the Anthropocene ended abruptly after the Second World War when a new technology push occurred, leading to the second stage: ‘the Great Acceleration’ (1945-2015) followed by the third: ‘Stewards of the Earth’. Here it is concluded that the notion of the Anthropocene reflects a hierarchical or individualistic perspective, often leading to a ‘business as usual’ management style, and ‘humanises’ the geological time scale. The use of this notion is not supported. However, it is already very popular in the media. This again might lead to overestimating the role of humans in nature, and might facilitate an even more destructive attitude towards it, through the application of geo-engineering. The latter could be opening another Pandora's box. Instead we should move to a more sustainable future in which human activities are better fine tuned to the environment that we are part of. In this respect, transition management is an interesting new paradigm.