This paper presents a LiDAR-equipped unmanned aerial vehicle (UAV) performing semi-autonomous wind-turbine blade inspection which includes traversing to the blade tip and back, while keeping constant ...relative distance and heading to the blade plane. Plane detection is performed applying the RANSAC method on a subset of the gathered pointcloud. Utilizing the relative distance to the inferred plane as well as its normal vector, the UAV is able to maintain a constant distance and heading towards the plane while moving in parallel with it. The proposed procedure performs successful wind-turbine blade inspections with minimal operator involvement. Inspection results include high-resolution blade images as well as a 3D model of the wind-turbine structure. Finally, to show the feasibility of this approach, simulations are performed on a wind-turbine model and experimental results are presented for an outdoor single-blade inspection scenario both on a mock-up setup and a full-scale wind-turbine blade. It is worth noting that the system's adequacy has been fully validated in real conditions on an operational wind farm.
In this article, we address a form of active perception characterized by curiosity-driven, open-ended exploration with intrinsic motivation, carried out by a group of agents. The multiple agents and ...a large number of possible actions are the main motivation for incorporating Multi-Agent Reinforcement Learning used to train a neural network in order to derive agent's policy. Partially Observable Markov Decision Process framework is used to accommodate the inaccuracy of sensors and probabilistic nature of agent's actions. The proposed method incorporates a consensus that derives the common belief vector, thus allowing each agent to make its decisions based on information acquired by all agents involved in the process of active perception. A well-known benchmark problem with a decentralized tiger scenario was used to demonstrate the possibility of the method to generate agents with different perceptual characteristics by simply changing the agents' reward function related to their intrinsic motivation. The main validation of the proposed approach was performed by using an example of multi-agent search mission. Final results are presented and discussed, and possible avenues for progress on open problems are identified.
This publication deals with the navigation of unmanned aerial vehicles (UAVs) moving in the magnetic field of two long, straight, parallel conductors, which is of high interest for several new ...technical applications. How the position and orientation of the UAV can be calculated using a minimal number of only three three-axis magnetometers are discussed. It is shown that the angles can be determined without the knowledge of the conductor currents and the magnetic field equations, but only by combining the sensor measurements with the rotation matrix and exploiting a characteristic property of the magnetic field. Furthermore, different strategies were investigated to determine the respective sensor positions. An analytical solution was derived from the nonlinear magnetic field equations, which promises a low computational time. It is shown that for a given sensor, several solutions exist, from which the correct one has to be selected. Therefore, a specific detection method is introduced. Once the solution is known, the UAV location can be determined. Finally, the overall algorithm was tested by simulations far from and near the conductors with superimposed typical magnetic noise.
In this paper we address the problem of trajectory following in an unknown environment with an unmanned aerial vehicle (UAV). The main goal is to safely follow the planned trajectory by avoiding ...obstacles. The proposed approach is suitable for aerial vehicles equipped with 2D or 3D sensors, such as LiDARs. We present a novel algorithm based on the conventional Artificial Potential Field (APF) called Augmented Artificial Potential Field (AAPF) that corrects the planned path to avoid obstacles. Our proposed algorithm uses a combination of two attractive forces and both normal and rotational repulsive forces to avoid obstacles and handle local minima problems. The smooth trajectory following achieved with the MPC tracker allows us to quickly change and re-plan the UAV path. Comparative simulation experiments have shown that our approach solves local minima problems in trajectory following and generates more efficient paths to avoid potential collisions with static obstacles compared to our previously developed algorithm for obstacle avoidance. The laboratory experimental evaluation results indicate that the algorithm can be deployed on a real UAV with limited computational power and real-time processing requirements.
This work presents the method based on the Partially Observable Markov Decision Processes (POMDP) and consensus protocol. The main idea is to share the belief and reach the consensus on the belief ...state in order to improve local decision making. To show that the belief update is important after reaching the observation alongside the average consensus, we examine novelty-biased consensus. The proposed method is applied on several benchmark problems and compared to an established method called Decentralized POMDP. Additionally, it is thoroughly examined in the simulation scenario. The results obtained in this work show that our method is efficient on the scenarios where agents explore the environment and it manages to execute mission in the scenarios where agents need to coordinate.
In this paper, we present a novel robotic system developed for researching collective social mechanisms in a biohybrid society of robots and honeybees. The potential for distributed coordination, as ...observed in nature in many different animal species, has caused an increased interest in collective behaviour research in recent years because of its applicability to a broad spectrum of technical systems requiring robust multi-agent control. One of the main problems is understanding the mechanisms driving the emergence of collective behaviour of social animals. With the aim of deepening the knowledge in this field, we have designed a multi-robot system capable of interacting with honeybees within an experimental arena. The final product, stationary autonomous robot units, designed by specificaly considering the physical, sensorimotor and behavioral characteristics of the honeybees (lat. Apis mallifera), are equipped with sensing, actuating, computation, and communication capabilities that enable the measurement of relevant environmental states, such as honeybee presence, and adequate response to the measurements by generating heat, vibration and airflow. The coordination among robots in the developed system is established using distributed controllers. The cooperation between the two different types of collective systems is realized by means of a consensus algorithm, enabling the honeybees and the robots to achieve a common objective. Presented results, obtained within ASSISIbf project, show successful cooperation indicating its potential for future applications.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This article presents a new control algorithm for the omnidirectional motion of a legged robot on uneven terrain based on an analytical kinematic solution without the use of Jacobians. In order to ...control the robot easily and efficiently in all situations, a simplified circle-based workspace approximation has been introduced. Foot trajectories for legged robot movement were generated on concentric circular paths around an analytically computed common centre of motion. This systematic motion model, together with new gait control variables that can be changed during legged robot motion, enabled the implementation of a new adaptive gait phase control algorithm, as well as the addition of algorithms for ground-level adaptation, 3-dimensional map-based step adjustment and fusion of all corrections to establish and/or maintain foot contact with the ground. The method being applicable to different legged robot designs was performed and tested on the laboratory prototype of a hexagonal hexapod robot, and the results of the experiments showed the practical value of the proposed adaptive yaw control method (available also as a video supplement).
The combined effects of environmental factors such as high winds and melting ice can cause transmission line conductors to vibrate at high amplitudes, resulting in damaged pole structures, cracked ...insulating strands, and short circuits. The manual installation of electrical spacers between the two power line conductors is currently the only way to prevent this, but due to the high-voltage environment, this operation is extremely dangerous for a human worker. As a solution to automate this operation, the autonomous installation of electrical spacers using a robotic manipulator is proposed. For this purpose, a design of a special end effector for the robotic installation of electrical spacers is proposed. The end effector prototype was produced and tested under laboratory conditions and then used for the autonomous installation of spacers on power lines. Its localization with respect to the power lines is based on measurements of the magnetic field generated by the alternating currents flowing through the power lines. To verify the feasibility of the proposed solution under laboratory conditions, the proposed end effector equipped with magnetometers was developed and mounted on a 6-axis Schunk LWA 4p robotic arm. The implemented autonomous installation sequence was successfully verified using a robot and a laboratory mock-up of power lines.
This paper presents a novel autonomous environmental monitoring methodology based on collaboration and collective decision-making among robotic agents in a heterogeneous swarm developed within the ...project subCULTron, tested in a realistic marine environment. The swarm serves as an underwater mobile sensor network for exploration and monitoring of large areas. Different robotic units enable outlier and fault detection, verification of measurements and recognition of environmental anomalies, and relocation of the swarm throughout the environment. The motion capabilities of the robots and the reconfigurability of the swarm are exploited to collect data and verify suspected anomalies, or detect potential sensor faults among the swarm agents. The proposed methodology was tested in an experimental setup in the field in two marine testbeds: the Lagoon of Venice, Italy, and Biograd an Moru, Croatia. Achieved experimental results described in this paper validate and show the potential of the proposed approach.
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