RotorS—A Modular Gazebo MAV Simulator Framework

Furrer, Fadri; Burri, Michael; Achtelik, Markus; Siegwart, Roland

doi:10.1007/978-3-319-26054-9_23

Cited by 469 publications

(239 citation statements)

References 4 publications

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“…Given a dual quaternion representation of the robots' position and orientation:q 1 = q 1 + 1 2 p 1 •q 1 andq 2 = q 2 + 1 2 p 2 • q 2 , where q i is the quaternion representing the orientation of robot i and p i = (0, x i , y i , z i ) represents its position, then the cluster can be specified with a set of two dual quaternionsq c ,q s , wherê Figure 7 shows the physical interpretation of the cluster dual quaternions of Eqs. (26,27), whereq c represents an average frame located between the two robot frames, andq s indicates the shape with a representation of the relative rotation and separation between robot frames. Furthermore, the inverse kinematics are defined byq 1 …”

Section: Robot Space Controllermentioning

confidence: 99%

See 1 more Smart Citation

Quaternions and Dual Quaternions: Singularity-Free Multirobot Formation Control

Mas

Kitts

2016

J Intell Robot Syst

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Cluster space control is a method of multirobot formation keeping that considers a group of robots to be a single entity, defining state variables to represent characteristics of the group, such as position, orientation, and shape. This technique, however, suffers from singularities when a minimal state representation is used. This paper presents three alternative implementations of this control approach that eliminate singularities through changes in the control architecture or through redundant formation definitions. These proposed solutions rely on quaternions, dual quaternions, and control implementations that produce singularity-free trajectories while maintaining a cluster level abstraction that allows for simple This work has been sponsored through USAIT Grant W911NF-14-1-0008, ITBACyT 2013-17, and Agencia Nacional de Promoción Científica y Tecnológica, FONCYT PICT 2014-2055.

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Section: Robot Space Controllermentioning

confidence: 99%

“…14). Each multicopter runs a Linux port of the PX4 autopilot firmware [27] with a MAVROS interface. This architecture allows a seamless transition of the proposed algorithms from the simulator to the actual hardware.…”

Section: Simulations In the Matlab Environmentmentioning

confidence: 99%

Quaternions and Dual Quaternions: Singularity-Free Multirobot Formation Control

Mas

Kitts

2016

J Intell Robot Syst

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“…We used RotorS [29] and Gazebo to validate our framework in simulation. We replaced the default controller provided in the simulator with our own described in Sec.…”

Section: Experiments a Simulation Environmentmentioning

confidence: 99%

Vision-based autonomous quadrotor landing on a moving platform

Falanga

Zanchettin

Simovic

et al. 2017

2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)

144

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Abstract-We present a quadrotor system capable of autonomously landing on a moving platform using only onboard sensing and computing. We rely on state-of-the-art computer vision algorithms, multi-sensor fusion for localization of the robot, detection and motion estimation of the moving platform, and path planning for fully autonomous navigation. Our system does not require any external infrastructure, such as motioncapture systems. No prior information about the location of the moving landing target is needed. We validate our system in both synthetic and real-world experiments using low-cost and lightweight consumer hardware. To the best of our knowledge, this is the first demonstration of a fully autonomous quadrotor system capable of landing on a moving target, using only onboard sensing and computing, without relying on any external infrastructure. SUPPLEMENTARY MATERIALVideo of the experiments: https://youtu.be/ Tz5ubwoAfNE

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“…Additionally, MAVROS provides a bridge for MAVProxy GCS, which will be useful to "Sense and Avoid" algorithm, since it relies mainly on MAVProxy GCS to stablish a communication and control gateway. The Rotors Simulation plugin provides Gazebo simulator the UAV kinematics and sensor readings (IMU and LiDAR / SoNAR) (Furrer, Burri, Achtelik, & Siegwart, 2016;Robotics, n.d.). With these plugins, it is possible to test "Sense and Avoid" algorithm by experiencing real UAV responses to algorithm decisions.…”

Section: D Simulationmentioning

confidence: 99%

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

Raimundo

Peres

Santos

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. "Sense and Avoid" algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk's flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the "Sense and Avoid" algorithm's overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and "Brake" mode on a real outdoor, proving its concepts.

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RotorS—A Modular Gazebo MAV Simulator Framework

Cited by 469 publications

References 4 publications

Quaternions and Dual Quaternions: Singularity-Free Multirobot Formation Control

Quaternions and Dual Quaternions: Singularity-Free Multirobot Formation Control

Vision-based autonomous quadrotor landing on a moving platform

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

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