Browsing by Author "Bernardo, Rodrigo"
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- Knowledge and tasks representation for an industrial robotic applicationPublication . Bernardo, Rodrigo; Farinha, Rodolfo; Gonçalves, PauloThe paper presents an implementation of knowledge representation and task representation, based on ontologies for an Industrial Robotic Application. The industrial application is to insert up to 56 small pins, e.g., sealants, in a harness box terminal for the automotive industry. The number of sealants and their insertion pattern vary significantly with the production requests. Based on the knowledge representation of the robot and also based on the tasks to be performed, plans are built and then sent to the robot controller based on the seal pattern production order. Moreover, the robotic system is capable to perform re-planning when an insertion error is reported by a machine vision system. The ontology-based approach was used to define the robot, the machine vision system, and the tasks that were needed to be performed by the robotic system. The robotic system was validated experimentally by showing its capability to correct seal insertion errors, while re-planning.
- A novel control architecture based on behavior trees for an omni-directional mobile robotPublication . Bernardo, Rodrigo; Sousa, João M.C.; Botto, Miguel Ayala; Gonçalves, PauloRobotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace.
- A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoningPublication . Bernardo, Rodrigo; Sousa, João M.C.; Gonçalves, PauloThe need to improve motion planning techniques for manipulator robots, and new effective strategies to manipulate different objects to perform more complex tasks, is crucial for various real-world applications where robots cooperate with humans. This paper proposes a novel framework that aims to improve the motion planning of a robotic agent (a manipulator robot) through semantic knowledge-based reasoning. The Semantic Web Rule Language (SWRL) was used to infer new knowledge based on the known environment and the robotic system. Ontological knowledge, e.g., semantic maps, were generated through a deep neural network, trained to detect and classify objects in the environment where the robotic agent performs. Manipulation constraints were deduced, and the environment corresponding to the agent’s manipulation workspace was created so the planner could interpret it to generate a collision-free path. For reasoning with the ontology, different SPARQL queries were used. The proposed framework was implemented and validated in a real experimental setup, using the planning framework ROSPlan to perform the planning tasks. The proposed framework proved to be a promising strategy to improve motion planning of robotics systems, showing the benefits of artificial intelligence, for knowledge representation and reasoning in robotics.
- Ontological framework to improve motion planning of manipulative agents through semantic knowledge-based reasoningPublication . Bernardo, Rodrigo; Sousa, João M.C.; Gonçalves, PauloThis paper describes the actions taken in developing a framework that aims to improve the motion planning of a manipulative robotic agent through reasoning based on semantic knowledge. The Semantic Web Rule Language (SWRL) was employed to draw new insights from the existing information about the robotic system and its environment. Recent ontology-based standards have been developed (IEEE 1872-2015; IEEE 1872.2-2021; IEEE 7007-2021), and others are currently under development (IEEE P1872.1; IEEE P1872.3) to improve robot performance in task execution. Ontological knowledge “semantic map" was generated using a deep neural network trained to detect and classify objects in the environment where the manipulator agent acts. Manipulation constraints were deduced, and the environment corresponding to the agent’s manipulation workspace was created so the planner could interpret it to generate a collision-free path. Several SPARQL queries were used to explore the semantic map and allow ontological reasoning. The proposed framework was implemented and validated in a real experimental setting, using the ROSPlan planning framework to perform the planning tasks. This ontology-based framework proved to be a promising strategy. E.g., it allows the robotic manipulative agent to interact with objects, e.g., to choose a mobile phone or a water bottle, using semantic information from the environment to solve the requested tasks.
- Ontology based robot reasoning in the elderly care domain - the EUROAGE projectsPublication . Gonçalves, Paulo; Bernardo, Rodrigo; Sousa, João M.C.This paper describes the actions developed and currently in development within the EUROAGE projects related to the ontology-based robot reasoning in the elderly care domain. Recent ontology-based standards were developed (IEEE 1872-2015; IEEE 1872.2-2021; IEEE 7007-2021), and others are currently in development (IEEE P1872.1; IEEE P1872.3) to improve robot performance while executing tasks. This is a very hot topic in current standardization efforts worldwide. The elderly care domain has special characteristics related to interactions with humans and robots living in the same workspace. As such, robots must also commit to social and ethical norms (IEEE 7007-2021). The robot and the actions it can perform in such interactions are defined according to the IEEE 1872-2015. Moreover, a semantic map of the environment was developed (using some concepts from the IEEE 1872.2- 2021) where the robot can interact with the elder and the sensors in the smart home. In this environment, an ontology-based platform was developed that allows the robot to interact with the objects, e.g., to pick a cell phone or bottle of water, using semantic information from that environment to solve demanded tasks. Ongoing efforts are underway to thoroughly add to the reasoning framework of the previously stated standards and the concepts from the IEEE 7007-2021 to ensure that the robot's actions are ethically and socially correct.
- Planning robotic agent actions using semantic knowledge for a home environmentPublication . Bernardo, Rodrigo; Sousa, João M.C.; Gonçalves, PauloAutonomous mobile robotic agents are increasingly present in highly dynamic environments, thus making the planning and execution of their tasks challenging. Task planning is vital in directing the actions of a robotic agent in domains where a causal chain could lock the agent into a dead-end state. This paper proposes a framework that integrates a domain ontology (home environment ontology) with a task planner (ROSPlan) to translate the objectives coming from a given agent (robot or human) into executable actions by a robotic agent.
- Survey on robotic systems for internal logisticsPublication . Bernardo, Rodrigo; Sousa, João M.C.; Gonçalves, PauloThe evolution of production systems has established major challenges in internal logistics. In order to overcome these challenges, new automation solutions have been developed and implemented. This paper is a literature review and analysis of selected scientific studies, which has as the main focus the existing solutions in robotics for internal logistics. The review aims to provide a broad perspective of the existing robotic systems for internal logistics to determine which research paths have been followed to date and highlight the current and future research directions. The survey has been subdivided into the following topics: localisation and path planning; task planning; optimisation and knowledge representation in robotic systems; and applications. The analysis of the works developed until the date of this review highlights the appearance of strategies in the different disciplines based on meta-heuristics. These are replacing the classical and heuristic approaches due to their limitations in dealing with a large amount of information in internal logistic systems. Due to the increase of information that robotic agents have to process, strategies based on semantic knowledge have been gaining prominence to make the domain knowledge explicit and eliminate ambiguities, allowing agents to reason and facilitate knowledge sharing between robotic agents and humans.