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- Robot Workspace Monitoring using a Blockchain-based 3D Vision ApproachPublication . Lopes, Vasco; Pereira, Nuno; Alexandre, LuísBlockchain has been used extensively for financial purposes, but this technology can also be beneficial in other contexts where multi-party cooperation, security and decentralization of the data is essential. Properties such as immutability, accessibility and non-repudiation and the existence of smart-contracts make blockchain technology very interesting in robotic contexts that require event registration or integration with Artificial Intelligence. In this paper, we propose a system that leverages blockchain as a ledger to register events and information to be processed by Oracles and uses smart-contracts to control robots by adjusting their velocity, or stopping them, if a person enters the robot working space without permission. We show how blockchain can be used in computer vision problems by interacting with multiple external parties, Oracles, that perform image analysis and how it is possible to use multiple smart-contracts for different tasks. The method proposed is shown in a scenario representing a factory environment, but since it is modular, it can be easily adapted and extended for other contexts, allowing for simple integration and maintenance.
- “Less is more”: Simplifying point clouds to improve grasping performancePublication . Lopes, Vasco; Alexandre, Luís; Fernandes, MiguelObject grasping is a task that humans do without major concerns. This results from self learning and by observing of other skilled humans doing such task with previous information. However, grasping novel objects in unknown positions for a robot is a complex task which encounters many problems, such as sub-optimal performance rates and the time consumption. In this paper we present a method that complements the state-of-the-art grasping algorithms with two segmentation steps, the first one which removes the largest planar surface in the point cloud of the world before the grasp detector receives them and the second one that complements this segmentation with another segmentation that calculates where the object is located and segments the point cloud by executing a crop around the object. The proposed method significantly improves the grasping success rate (100% improvement over the baseline approach) and simultaneously is able to reduce the time consumption by 23%.
- Improving Grasping Performance by Segmentation of Large Planar SurfacePublication . Lopes, Vasco; Alexandre, LuísGrasping objects is a task that humans do without major concerns. This results from learning and observing other skilled humans doing such task and with previous information, unconsciously, we know how to pick up different types of objects. However, grasping novel objects in unknown positions for a robot is a complex task which encounters many problems, such as the performance rates that are not perfect and the time consumption. In this paper we present a method that complements the state-ofthe- art grasping by removing the largest planar surface of the image of the world before the grasp detector receives them. The proposed method improves the performance rate and is also capable of reducing the time consumption.
- uPATO Mobile - Network ModulePublication . Silva, Frutuoso; Lopes, Vasco; Ribeiro, José; Martins, FernandoTeam sports analysis can be done using network analysis tools if the interactions between teammates are recorded. However, no application was specifically developed to team sports, that allows to import, compute and export data, as far as we know. Based on that, we developed a new application for network analysis in team sports. The Ultimate Performance Analysis Tool (uPATO) allows codifying, importing, visualising, computing measures and exporting data from the observed games. Thus, the user can use a single application to codify the network that emerges from the game and analyse it. In this paper, we will present the mobile application uPATO that allows using an Android device to codify and analyse networks in team sports. This application extends the use of the uPATO tool for outdoor environments, making easier their use in the real scenarios with a mobile device, for example, in official games or during the training sessions. Finally, data of a real game will be used to test the network measures implemented and to show the values that can be obtained.
- An Overview of Blockchain Integration with Robotics and Artificial IntelligencePublication . Lopes, Vasco; Alexandre, LuísBlockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn't yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that try to leverage the power of blockchain into robotic systems, to improve AI services or to solve problems that are present in the major blockchains, which can lead to the ability of creating robotic systems with increased capabilities and security. We present an overview, discuss the methods and conclude the paper with our view on the future of the integration of these technologies.
- An Overview of Blockchain Integration with Robotics and Artificial IntelligencePublication . Lopes, Vasco; Alexandre, LuísBlockchain technology is growing everyday at a fast-passed rhythm and it is possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there is not yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that try to leverage the power of blockchain into robotic systems, to improve AI services, or to solve problems that are present in the major blockchains, which can lead to the ability of creating robotic systems with increased capabilities and security. We present an overview, discuss the methods, and conclude the paper with our view on the future of the integration of these technologies.
- Controlling Robots using Artificial Intelligence and a Consortium BlockchainPublication . Lopes, Vasco; Alexandre, Luís; Pereira, NunoBlockchain is a disruptive technology that is normally used within financial applications, however it can be very beneficial also in certain robotic contexts, such as when an immutable register of events is required. Among the several properties of Blockchain that can be useful within robotic environments, we find not just immutability but also decentralization of the data, irreversibility, accessibility and non-repudiation. In this paper, we propose an architecture that uses blockchain as a ledger and smart-contract technology for robotic control by using external parties, Oracles, to process data. We show how to register events in a secure way, how it is possible to use smart-contracts to control robots and how to interface with external Artificial Intelligence algorithms for image analysis. The proposed architecture is modular and can be used in multiple contexts such as in manufacturing, network control, robot control, and others, since it is easy to integrate, adapt, maintain and extend to new domains.
- Detecting Robotic Anomalies using RobotChainPublication . Lopes, Vasco; Alexandre, LuísRobotic events can provide notable amounts of information regarding a robot’s status, which can be extrapolated to detect productivity, anomalies, malfunctions and used for monitorization. However, when problems occur in sensitive environments like a factory, the logs of a machine may be discarded because they are susceptible to chances and malicious intents. In this paper we propose to use RobotChain for anomaly detection. RobotChain is a method to securely register robotic events, using a blockchain, which ensures that once an event gets registered on it, it’s secured and cannot be tampered with. We show how this system can be leveraged with the module for anomaly detection, that uses the information contained on the blockchain to detect anomalies on a UR3 robot.
- RobotChain: Artificial Intelligence on a Blockchain using Tezos TechnologyPublication . Lopes, Vasco Ferrinho; Alexandre, Luís Filipe Barbosa de AlmeidaBlockchain technology is not only growing everyday at a fast-passed rhythm, but it is also a disruptive technology that has changed how we look at financial transactions. By providing a way to trust an unknown network and by allowing us to conduct transactions without the need for a central authority, blockchain has grown exponentially. Moreover, blockchain also provides decentralization of the data, immutability, accessibility, non-repudiation and irreversibility properties that makes this technology a must in many industries. But, even thought blockchain provides interesting properties, it has not been extensively used outside the financial scope. Similarly, robots have been increasingly used in factories to automate tasks that range from picking objects, to transporting them and also to work collaboratively with humans to perform complex tasks. It is important to enforce that robots act between legal and moral boundaries and that their events and data are securely stored and auditable. This rarely happens, as robots are programmed to do a specific task without certainty that that task will always be performed correctly and their data is either locally stored, without security measures, or disregarded. This means that the data, especially logs, can be altered, which means that robots and manufacturers can be accused of problems that they did not cause. Henceforth, in this work, we sought to integrate blockchain with robotics with the goal to provide enhanced security to robots, to the data and to leverage artificial intelligence algorithms. By doing an extensive overview of the methods that integrate blockchain and artificial intelligence or robotics, we found that this is a growing field but there is a lack of proposals that try to improve robotic systems by using blockchain. It was also clear that most of the existing proposals that integrate artificial intelligence and blockchain, are focused on building marketplaces and only use the latter to storage transactions. So, in this document, we proposed three different methods that use blockchain to solve different problems associated with robots. The first one is a method to securely store robot logs in a blockchain by using smart-contracts as storage and automatically detect when anomalies occur in a robot by using the data contained in the blockchain and a smart-contract. By using smart-contracts, it is assured that the data is secure and immutable as long as the blockchain has enough peers to participate in the consensus process. The second method goes beyond registering events to also register information about external sensors, like a camera, and by using smart-contracts to allow Oracles to interact with the blockchain, it was possible to leverage image analysis algorithms that can detect the presence of material to be picked. This information is then inserted into a smart-contract that automatically defines the movement that a robot should have, regarding the number of materials present to be picked. The third proposal is a method that uses blockchain to store information about the robots and the images derived from a Kinect. This information is then used by Oracles that check if there is any person located inside a robot workspace. If there is any, this information is stored and different Oracles try to identify the person. Then, a smart-contract acts appropriately by changing or even stopping the robot depending on the identity of the person and if the person is located inside the warning or the critical zone surrounding the robot. With this work, we show how blockchain can be used in robotic environments and how it can beneficial in contexts where multi-party cooperation, security, and decentralization of the data is essential. We also show how Oracles can interact with the blockchain and distributively cooperate to leverage artificial intelligence algorithms to perform analysis in the data that allow us to detect robotic anomalies, material in images and the presence of people. We also show that smart-contracts can be used to perform more tasks than just serve the purpose of automatically do monetary transactions. The proposed architectures are modular and can be used in multiple contexts such as in manufacturing, network control, robot control, and others since they are easy to integrate, adapt, maintain and extend to new domains. We expect that the intersection of blockchain and robotics will shape part of the future of robotics once blockchain is more widely used and easy to integrate. This integration will be very prominent in tasks where robots need to behave under certain constraints, in swarm robotics due to the fact that blockchain offers global information and in factories because the actions undertaken by a robot can easily be extended to the rest of the robots by using smart-contracts.
- Real-time 2D–3D door detection and state classification on a low-power devicePublication . Ramôa, João Gaspar; Lopes, Vasco; Alexandre, Luís; Mogo, SandraIn this paper, we propose three methods for door state classifcation with the goal to improve robot navigation in indoor spaces. These methods were also developed to be used in other areas and applications since they are not limited to door detection as other related works are. Our methods work ofine, in low-powered computers as the Jetson Nano, in real-time with the ability to diferentiate between open, closed and semi-open doors. We use the 3D object classifcation, PointNet, real-time semantic segmentation algorithms such as, FastFCN, FC-HarDNet, SegNet and BiSeNet, the object detection algorithm, DetectNet and 2D object classifcation networks, AlexNet and GoogleNet. We built a 3D and RGB door dataset with images from several indoor environments using a 3D Realsense camera D435. This dataset is freely available online. All methods are analysed taking into account their accuracy and the speed of the algorithm in a low powered computer. We conclude that it is possible to have a door classifcation algorithm running in real-time on a low-power device.