This paper presents a family of autonomous Unmanned Aerial Vehicles (UAVs) platforms designed for a diverse range of indoor and outdoor applications. The proposed UAV design is highly modular in terms of used actuators, sensor configurations, and even UAV frames. This allows to achieve, with minimal effort, a proper experimental setup for single, as well as, multi-robot scenarios. Presented platforms are intended to facilitate the transition from simulations, and simplified laboratory experiments, into the deployment of aerial robots into uncertain and hard-to-model real-world conditions. We present mechanical designs, electric configurations, and dynamic models of the UAVs, followed by numerous recommendations and technical details required for building such a fully autonomous UAV system for experimental verification of scientific achievements. To show strength and high variability of the proposed system, we present results of tens of completely different real-robot experiments in various environments using distinct actuator and sensory configurations.

MRS Modular UAV Hardware Platforms for Supporting Research in Real-World Outdoor and Indoor Environments

An application of stereo thermal vision to perform preliminary inspection operations of electrical power lines by a particular class of small Unmanned Aerial Vehicles (UAVs), aka Micro Unmanned Aerial Vehicles (MAVs), is presented in this paper. The proposed hardware and software setup allows the detection of overheated power equipment, one of the major causes of power outages. The stereo vision complements the GPS information by finely detecting the potential source of damage while also providing a measure of the harm extension. The reduced sizes and the light weight of the vehicle enable to survey areas otherwise difficult to access with standard UAVs. Gazebo simulations and real flight experiments demonstrate the feasibility and effectiveness of the proposed setup.

An Application of Stereo Thermal Vision for Preliminary Inspection of Electrical Power Lines by MAVs

Integration of Visual Inertial Odometry (VIO) methods into a modular control system designed for deployment of Unmanned Aerial Vehicles (UAVs) and teams of cooperating UAVs in real-world conditions are presented in this paper. Reliability analysis and fair performance comparison of several methods integrated into a control pipeline for achieving full autonomy in real conditions is provided. Although most VIO algorithms achieve excellent localization precision and negligible drift on artificially created datasets, the aspects of reliability in non-ideal situations, robustness to degraded sensor data, and the effects of external disturbances and feedback control coupling are not well studied. These imperfections, which are inherently present in cases of real-world deployment of UAVs, negatively affect the ability of the most used VIO approaches to output a sensible pose estimation. We identify the conditions that are critical for a reliable flight under VIO localization and propose workarounds and compensations for situations in which such conditions cannot be achieved. The performance of the UAV system with integrated VIO methods is quantitatively analyzed w.r.t. RTK ground truth and the ability to provide reliable pose estimation for the feedback control is demonstrated onboard a UAV that is tracking dynamic trajectories under challenging illumination.

Deployment of Reliable Visual Inertial Odometry Approaches for Unmanned Aerial Vehicles in Real-world Environment

This paper investigates the problem of task assignment and trajectory generation for the installation of bird diverters with a ﬂeet of multirotors leveraging on Signal Temporal Logic (STL) speciﬁcations. We extend our previous motion planner to compute feasible and constrained trajectories, taking into account payload capacity limitations and recharging constraints. The proposed planner ensures the continuity of the operation, while guaranteeing compliance with safety requirements and mission fulﬁllment. Additionally, an event-based replanning strategy is proposed to react to unforeseen failures. An energy minimization term is also considered to implicitly save multirotor ﬂight time during installation operations. Numerical simulations in MATLAB, Gazebo, and ﬁeld experiments demonstrate the performance of the approach and its validity in mock-up scenarios.

A Signal Temporal Logic Motion Planner for Bird Diverter Installation Tasks with Multi-Robot Aerial Systems

This paper presents a family of autonomous Unmanned Aerial Vehicles (UAVs) platforms designed for a diverse range of indoor and outdoor applications. The proposed UAV design is highly modular in terms of used actuators, sensor configurations, and even UAV frames. This allows to achieve, with minimal effort, a proper experimental setup for single, as well as, multi-robot scenarios. Presented platforms are intended to facilitate the transition from simulations, and simplified laboratory experiments, into the deployment of aerial robots into uncertain and hard-to-model real-world conditions. We present mechanical designs, electric configurations, and dynamic models of the UAVs, followed by numerous recommendations and technical details required for building such a fully autonomous UAV system for experimental verification of scientific achievements. To show strength and high variability of the proposed system, we present results of tens of completely different real-robot experiments in various environments using distinct actuator and sensory configurations. 

This letter concerns optimal power transmission line inspection formulated as a proposed generalization of the traveling salesman problem for a multi-route one-depot scenario. The problem is formulated for an inspection vehicle with a limited travel budget. Therefore, the solution can be composed of multiple runs to provide full coverage of the given power lines. Besides, the solution indicates how many vehicles can perform the inspection in a single run. The optimal solution of the problem is solved by the proposed Integer Linear Programming (ILP) formulation, which is, however, very computationally demanding. Therefore, the computational requirements are addressed by the combinatorial metaheuristic. The employed greedy randomized adaptive search procedure is significantly less demanding while providing competitive solutions and scales better with the problem size than the ILP-based approach. The proposed formulation and algorithms are demonstrated in a real-world scenario to inspect power line segments at the electrical substation.

Multi-Tour Set Traveling Salesman Problem in Planning Power Transmission Line Inspection

Repeated exploration of a water surface to detect objects of interest and their subsequent monitoring is important in search-and-rescue or ocean clean-up operations. Since the location of any detected object is dynamic, we propose to address the combined surface exploration and monitoring of the detected objects by modeling spatio-temporal reward states and coordinating a team of vehicles to collect the rewards. The model characterizes the dynamics of the water surface and enables the planner to predict future system states. The state reward value relevant to the particular water surface cell increases over time and is nullified by being in a sensor range of a vehicle. Thus, the proposed multi-vehicle planning approach is to minimize the collective value of the dynamic model reward states. The purpose is to address vehicles' motion constraints by using model predictive control on receding horizon, thus fully exploiting the utilized vehicles' motion capabilities. Based on the evaluation results, the approach indicates improvement in a solution to the kinematic orienteering problem and the team orienteering problem in the monitoring task compared to the existing solutions. The proposed approach has been experimentally verified, supporting its feasibility in real-world monitoring tasks.

Multi-vehicle Dynamic Water Surface Monitoring

This paper concerns fault-tolerant power transmission line inspection planning as a generalization of the multiple traveling salesmen problem. The addressed inspection planning problem is formulated as a single-depot multiple-vehicle scenario, where the inspection vehicles are constrained by the battery budget limiting their inspection time. The inspection vehicle is assumed to be an autonomous multi-copter with a wide range of possible flight speeds influencing battery consumption. The inspection plan is represented by multiple routes for vehicles providing full coverage over inspection target power lines. On an inspection vehicle mission interruption, which might happen at any time during the execution of the inspection plan, the inspection is re-planned using the remaining vehicles and their remaining battery budgets. Robustness is introduced by choosing a suitable cost function for the initial plan that maximizes the time window for successful re-planning. It enables the remaining vehicles to successfully finish all the inspection targets using their respective remaining battery budgets. A combinatorial metaheuristic algorithm with various cost functions is used for planning and fast re-planning during the inspection.

Frantisek Nekovar

Papers

Multi-Tour Set Traveling Salesman Problem in Planning Power Transmission Line Inspection

Multi-vehicle Dynamic Water Surface Monitoring

Vehicle Fault-Tolerant Robust Power Transmission Line Inspection Planning