This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor co...
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This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor complex tasks. Indeed, a wide range of sensors composes the robot and enables it to perceive vast workspaces, reach distant targets, and face the uncertainties of the real world. Precise object detection is also guaranteed, essential to manipulate objects of different shapes and materials. Moreover, a customized 3-finger gripper makes the gripping mode suitable for any lightweight object. Two modalities are proposed: autonomous and teleoperated, letting both unskilled and skilled human operators easily adapt the system to complete personalized tasks. The paper exhaustively describes RUR53 architecture and demonstrates its good performance while executing both indoor and outdoor navigation and manipulation tasks. A specific case study is described where the proposed modular architecture allows to easily switch to a semi-teleoperated mode: the 2017 Mohamed Bin Zayed International robotics Challenge, where our team ranked third in the Grand Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).
This paper describes the image selection method by multimodal detection for improving the computational efficiency of three-dimensional (3D) reconstruction based on images in a time-series. To decrease the calculation...
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This paper describes the image selection method by multimodal detection for improving the computational efficiency of three-dimensional (3D) reconstruction based on images in a time-series. To decrease the calculation time of the 3D reconstruction, an adequate selection from the images is required. For this reason, we introduced multimodal detection by a statistical test on the image selection process, and then applied it to soundness evaluation of the displacements based on the optical flow between images acquired by a camera. The results suggest that suitable images can be extracted from the images in a time-series for decreasing the calculation time of the 3D reconstruction. Therefore, the suitable images selected by the proposed method contributed to efficiently performing the 3D reconstruction.
Virtual environment-assisted teleoperation has great potential as a human-robot interaction paradigm for field robotic systems, in particular when combined with elements of automation. Unstructured outdoor environment...
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Virtual environment-assisted teleoperation has great potential as a human-robot interaction paradigm for field robotic systems, in particular when combined with elements of automation. Unstructured outdoor environments present a complex problem with many challenging elements. For the specific application of forestry machines, we investigate which steps are required in order to implement such a system, what potential benefits there are, and how individual components can be adapted to efficiently assist forestry machine operators in their daily work in the near future. An experimental prototype of a teleoperation system with virtual environment- based feedback is constructed using a scenario-based design process. The feasibility of the implementation is partly verified through experimental studies.
Electrically powered robots are seeing increased adoption for field robotics applications. These applications typically require the platforms be deployed for extended periods, or traverse large distances. Power modell...
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Electrically powered robots are seeing increased adoption for field robotics applications. These applications typically require the platforms be deployed for extended periods, or traverse large distances. Power modelling therefore becomes important, as knowing the energy costs of operation is necessary for the estimation of maximum range and operating time, and the generation of energy-efficient plans. In this paper, we present a physics-based power model for the Swagbot platform--an omnidirectional electric field robot--which can be calibrated from a combination of GPS and proprioceptive data gathered throughout the course of normal operations. This model is then experimentally verified via endurance testing performed on cattle properties featuring uneven terrain. The model was demonstrated to predict the energy consumption for a pasture survey and a weed detection task to within 5% of the measured value.
Due to the limitations of electromagnetic signals, underwater scenarios increase the complexity of developing accurate navigation systems. In the last decades, Ultra-Short BaseLine (USBL) positioning systems have been...
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Due to the limitations of electromagnetic signals, underwater scenarios increase the complexity of developing accurate navigation systems. In the last decades, Ultra-Short BaseLine (USBL) positioning systems have been widely and efficiently used for Autonomous Underwater Vehicles (AUVs) localization, endorsing to be a suitable solution to limit the navigation drift without requiring periodic surfacing for Global Positioning System (GPS) resets. Typically, in the localization context, USBL measurements are exploited as observations within the on-board navigation filter where, most of the time, Extended Kalman Filter (EKF) or Unscented Kalman Filter (UKF) solutions are employed. In a break-away from the above-mentioned approaches, in this study, the localization task is solved as a Maximum A Posteriori (MAP) estimation problem. The presented solution is validated through the use of data gathered in October 2020 during EUMarineRobots (EUMR) tests in La Spezia (Italy) within the activities of the SEALab, the joint research laboratory between the Naval Support and Experimentation Center (Centro di Supporto e Sperimentazione Navale, CSSN) of the Italian Navy and the Interuniversity Center of Integrated Systems for the Marine Environment (ISME).
Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (C...
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Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (Collaborative SubTerranean Autonomous Robots) in the Sub-T challenge, this work establishes a novel traversable graph-based exploration strategy that utilizes frontiers for local navigation and a fast collision risk-aware graph building for global navigation. The exploration strategy extracts frontiers in an unknown area that contribute to safe navigation while maximizing information gain for the robot. The exploration problem is further bifurcated into local and global exploration for faster decision-making at junctions with the goal of rapidly exploring the area. The local exploration guarantees collision-free straight-line paths to informative frontiers for rapid forward navigation, while global re-positioning utilizes a traversable graph subject to geometrical collision checks within the occupancy map. The pathfinding in a graph is addressed using a heuristic, which combines risk margins and travel costs to assist in short yet safe paths to the global frontier in case of a dead end in local exploration. The presented exploration strategy is developed with the goal of making exploration algorithms platform agnostic in order to be able to use it with aerial, as well as ground robots. The proposed method is also evaluated against different state-of-the-art exploration planners in simulated fixed-time budget-based exploration missions on an Unmanned Aerial Vehicle (UAV) in order to benchmark the capabilities and highlight the novelty.
Autonomous vehicles need to recognize and localize obstacles in their environment in order to avoid collisions. This paper presents a novel method for estimating the misalignment between a simultaneous localization an...
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Autonomous vehicles need to recognize and localize obstacles in their environment in order to avoid collisions. This paper presents a novel method for estimating the misalignment between a simultaneous localization and mapping (SLAM) map and and an Earth-fixed coordinate systems in order to allow highly accurate global localization of obstacles in the environment. The sensors used for this method are an Inertial Measurement Unit (IMU), satellite-based positioning (GNSS/GPS) and both 2D and 3D lidar sensors. Experimental validation on a tractor shows that the typical global localization accuracy is in the range of 100 mm…150 mm.
Orchard navigation using sensor-based localization and flexible mission management facilitates successful missions independent of the Global Positioning System (GPS). This is especially important while driving between...
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Orchard navigation using sensor-based localization and flexible mission management facilitates successful missions independent of the Global Positioning System (GPS). This is especially important while driving between tight tree rows where the GPS coverage is poor. This paper suggests localization based on an a priori map of the tree rows, a laser scanner based tree row detection, detecting both the row line and the row ends. The localization is combined with mission objectives in a rule-based inference interpreter. This rule-based mission handler combines the functional modules: localization, obstacle avoidance, path planning and drive control. The system is tested successfully using a Hako 20 kW tractor during autonomous missions in both cherry and apple orchards with mission length of up to 2.3 km including the headland turns.
DORIS is a mobile robot for remote supervision, diagnosis, and data acquisition on offshore facilities. The proposed system is composed of a rail-guided robot capable of carrying different sensors through the inspecte...
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DORIS is a mobile robot for remote supervision, diagnosis, and data acquisition on offshore facilities. The proposed system is composed of a rail-guided robot capable of carrying different sensors through the inspected area. This paper presents a general overview of the robot, and a description of the developed embedded electronics, power supply system and software architecture. The results with teleoperated navigation validate the concepts considered so far and rise several challenges for future works.
This paper takes a broad look at the evolution of field Robotic Technology, beginning with the need to develop robotic systems for use in unstructured environments, their current performance niches, and their future o...
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This paper takes a broad look at the evolution of field Robotic Technology, beginning with the need to develop robotic systems for use in unstructured environments, their current performance niches, and their future opportunities to impact the world in constrution, subsea, space, nuclear, mining, and military applications. It concludes that the evolution of field robotic technology is inevitable: new robotic forms will emerge with the capability and the strategic competence to construct, maintain, and demolish, but the evolution of field robotics will not culminate in a single form. Rather, classes of robots will emerge for classes of work within classes of constraints.
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