Unmanned Ground Vehicles for Smart Farms

Forecasts of world population increases in the coming decades demand new production processes that are more efficient, safer, and less destructive to the environment. Industries are working to fulfill this mission by developing the smart factory concept. The agriculture world should follow industry leadership and develop approaches to implement the smart farm concept. One of the most vital elements that must be configured to meet the requirements of the new smart farms is the unmanned ground vehicles (UGV). Thus, this chapter focuses on the characteristics that the UGVs must have to function efficiently in this type of future farm. Two main approaches are discussed: automating conventional vehicles and developing specifically designed mobile platforms. The latter includes both wheeled and wheel-legged robots and an analysis of their adaptability to terrain and crops

Marine Vessel Inspection as a Novel Field for Service Robotics: A Contribution to Systems, Control Methods and Semantic Perception Algorithms.

This cumulative thesis introduces a novel field for service robotics: the inspection of marine vessels using mobile inspection robots. In this thesis, three scientific contributions are provided and experimentally verified in the field of marine inspection, but are not limited to this type of application. The inspection scenario is merely a golden thread to combine the cumulative scientific results presented in this thesis. The first contribution is an adaptive, proprioceptive control approach for hybrid leg-wheel robots, such as the robot ASGUARD described in this thesis. The robot is able to deal with rough terrain and stairs, due to the control concept introduced in this thesis. The proposed system is a suitable platform to move inside the cargo holds of bulk carriers and to deliver visual data from inside the hold. Additionally, the proposed system also has stair climbing abilities, allowing the system to move between different decks. The robot adapts its gait pattern dynamically based on proprioceptive data received from the joint motors and based on the pitch and tilt angle of the robot's body during locomotion. The second major contribution of the thesis is an independent ship inspection system, consisting of a magnetic wall climbing robot for bulkhead inspection, a particle filter based localization method, and a spatial content management system (SCMS) for spatial inspection data representation and organization. The system described in this work was evaluated in several laboratory experiments and field trials on two different marine vessels in close collaboration with ship surveyors. The third scientific contribution of the thesis is a novel approach to structural classification using semantic perception approaches. By these methods, a structured environment can be semantically annotated, based on the spatial relationships between spatial entities and spatial features. This method was verified in the domain of indoor perception (logistics and household environment), for soil sample classification, and for the classification of the structural parts of a marine vessel. The proposed method allows the description of the structural parts of a cargo hold in order to localize the inspection robot or any detected damage. The algorithms proposed in this thesis are based on unorganized 3D point clouds, generated by a LIDAR within a ship's cargo hold. Two different semantic perception methods are proposed in this thesis. One approach is based on probabilistic constraint networks; the second approach is based on Fuzzy Description Logic and spatial reasoning using a spatial ontology about the environment

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Hybrid locomotion for agricultural robotic platform : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Engineering at Massey University, Turitea Campus, Palmerston North, New Zealand

The following Figures were removed for copyright reasons: Figs 2 & 35 (=Stentz et al., 2015 Fig 1), Figs 4 & 41 (=Michaud et al., 2005 Fig 15), Fig 16 (=Bakker et al., 2010 Fig 4), Fig 25 (=Siegwart et al., 2002 Fig 14) & Fig 30 (=De Santos et al., 2007 Fig 1).The New Zealand dairy industry is an important component of the New Zealand economy with an annual income of 14 billion dollars. Due to its significance it is important that new technology is developed to further the industry and increase efficiency. Many precision agricultural robots and prototypes were reviewed in this thesis and the topic of hybrid locomotion was discussed. Using methods of hybrid locomotion, a design of a prototype with non-complex mechanisms has been presented in this thesis. Hybrid locomotion is a popular field among robotics where researchers and engineers design robots that has more than one mode of locomotion. By incorporating hybrid locomotion, it allows the robot to tackle unique terrains which most single locomotion style robots cannot. The prototype presented in this thesis uses the track leg hybrid locomotion style. This design allows the robot platform to get much closer to the ground which will allow the platform to carry sensors that needs to be within proximity to the ground to operate. The design allows the prototype to have two modes of locomotion, track mode and leg mode. IoT is the new trend in the world that can be used to remotely monitor and control devices. IoT in agriculture was also reviewed in this thesis and an IoT gateway circuit was designed and presented. A prototype was manufactured, which uses the cellular network and can receive data from sensors connected via 6 ADC inputs and the RS485 communication method which will allow the platform to carry various different sensors for data acquisition. The final product is intended to be used in a typical New Zealand dairy or life stock farm to gather parameters such as grass health and soil parameters which will be useful to researchers for data analysis and develop new fertiliser and grass types for animals in a farm. The IoT gateway prototype in this thesis will allow the robot to be fully autonomous and will allow the prototype to be operated remotely. The final prototype is intended to have bidirectional communication where the user can send commands and receive data remotely. This concept has the potential to be a very useful tool to agricultural researchers and scientists in agriculture. The preliminary testing showed promising results, but also suggested that more development and testing is necessary to further validate the design concept. The tests and results are presented and discussed in this thesis

Agronomy

Climate change is a serious threat to field crop production and food security. It has negative effects on food, water, and energy security due to change in weather patterns and extreme events such as floods, droughts, and heat waves, all of which reduce crop productivity. Over six chapters, this book presents a comprehensive picture of the importance of agronomy as it relates to the United Nations’ Sustainable Development Goals. With an emphasis on the goals of Zero Hunger and Climate Change, this volume examines sustainable agronomic practices to increase crop productivity and improve environmental health

An Intelligent Architecture for Legged Robot Terrain Classification Using Proprioceptive and Exteroceptive Data

In this thesis, we introduce a novel architecture called Intelligent Architecture for Legged Robot Terrain Classification Using Proprioceptive and Exteroceptive Data (iARTEC ) . The proposed architecture integrates different terrain characterization and classification with other robotic system components. Within iARTEC , we consider the problem of having a legged robot autonomously learn to identify different terrains. Robust terrain identification can be used to enhance the capabilities of legged robot systems, both in terms of locomotion and navigation. For example, a robot that has learned to differentiate sand from gravel can autonomously modify (or even select a different) path in favor of traversing over a better terrain. The same knowledge of the terrain type can also be used to guide a robot in order to avoid specific terrains. To tackle this problem, we developed four approaches for terrain characterization, classification, path planning, and control for a mobile legged robot. We developed a particle system inspired approach to estimate the robot footâ ground contact interaction forces. The approach is derived from the well known Bekkerâ s theory to estimate the contact forces based on its point contact model concepts. It is realistically model real-time 3-dimensional contact behaviors between rigid body objects and the soil. For a real-time capable implementation of this approach, its reformulated to use a lookup table generated from simple contact experiments of the robot foot with the terrain. Also, we introduced a short-range terrain classifier using the robot embodied data. The classifier is based on a supervised machine learning approach to optimize the classifier parameters and terrain it using proprioceptive sensor measurements. The learning framework preprocesses sensor data through channel reduction and filtering such that the classifier is trained on the feature vectors that are closely associated with terrain class. For the long-range terrain type prediction using the robot exteroceptive data, we present an online visual terrain classification system. It uses only a monocular camera with a feature-based terrain classification algorithm which is robust to changes in illumination and view points. For this algorithm, we extract local features of terrains using Speed Up Robust Feature (SURF). We encode the features using the Bag of Words (BoW) technique, and then classify the words using Support Vector Machines (SVMs). In addition, we described a terrain dependent navigation and path planning approach that is based on E* planer and employs a proposed metric that specifies the navigation costs associated terrain types. This generated path naturally avoids obstacles and favors terrains with lower values of the metric. At the low level, a proportional input-scaling controller is designed and implemented to autonomously steer the robot to follow the desired path in a stable manner. iARTEC performance was tested and validated experimentally using several different sensing modalities (proprioceptive and exteroceptive) and on the six legged robotic platform CREX. The results show that the proposed architecture integrating the aforementioned approaches with the robotic system allowed the robot to learn both robot-terrain interaction and remote terrain perception models, as well as the relations linking those models. This learning mechanism is performed according to the robot own embodied data. Based on the knowledge available, the approach makes use of the detected remote terrain classes to predict the most probable navigation behavior. With the assigned metric, the performance of the robot on a given terrain is predicted. This allows the navigation of the robot to be influenced by the learned models. Finally, we believe that iARTEC and the methods proposed in this thesis can likely also be implemented on other robot types (such as wheeled robots), although we did not test this option in our work

Possibility of hazardous environment monitoring

Tato bakalářská práce se zabývá mobilní robotikou a jejím využitím v průmyslu, konkrétně v průmyslu energetickém. Důraz je kladen na schopnost pohybu a překonávání překážek. Cílem této práce je poskytnout čtenáři základní přehled o mobilní robotice, o podvozcích, jejich druzích, výhodách a účelu použití. V druhé častí je popsán návrh koncepce podvozku mobilního monitorovacího zařízení pro zadanou aplikaci. Následuje návrh koncepce polohovacího zařízení na kterém bude umístěno zařízení pro monitorování. Tyto koncepce mají za účel nastínit možné řešení práce a byly řešeny s ohledem na funkčnost zařízení a cenu. Výstupem je předpokládané mobilní monitorovací zařízení, které by mělo být schopné plnit zadané úkoly.This bachelor’s thesis is about mobile robotics and usage it in electricity industry. First part solve ability of taking the fences and provide basic facts about mobile robotics, kind of chassis and purpose of usage to reader. Second part includes concepts of truck and position device with monitoring system. This concepts solve submission with reference to utility of monitoring device, mobile robot and price. Output of this work is constructive solving of mobile monitoring robot.

Indoor And Outdoor Real Time Information Collection in Disaster Scenario

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario. The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers. The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on A­* is also proposed

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

Development and Evaluation of a Human-Robot Interface for an Autonomous All-Terrain Transportation Vehicle in order to Localize, Track and Follow a Human.

Full solutions for automatic transportation vehicles in unstructured environments are restricted to military applications, although possible mission scenarios exist for civil and space applications. In this thesis, a user-friendly, human-robot interface is implemented for an all-terrain electric vehicle. The interface allows the vehicle to follow a moving user autonomously by combining 3D LIDAR measurements with intensity images. The method detects clusters within the LIDAR scan that match the human appearance and resolves potential ambiguities based on image tracking results. The interface can be controlled using different input devices. A detailed evaluation compares the input devices, analyzes the implemented algorithms, and validates the overall system behavior outdoor under real-world conditions. The developed system is able to follow its user as long as he is completely visible