Simulation plays a significant role in development and deployment of robotics systems. Depending on the planned tasks, different functionalities shift into focus. For mobile robotics systems using the Robot Operating System (ROS), Gazebo has been the goto solution for simulating behavior, sensors, and interaction with environments for many years. With the availability of numerous novel solutions, a comparison of the different strengths from a use-case perspective becomes necessary. In our paper, we compare Gazebo and NVIDIAs Isaac Sim in the context of ROS-based autonomous mobile robots. Special attention is given to the integration of the simulators in the ROS-environment and their ability in regards to sensor simulation. This paper aims to provide a comparison between different features in Gazebo and NVIDIA Isaac Sim for simulating mobile robots and sensor systems.
Duetotheavailabilityof highly efficient unmanned aircraft (UA) and the advancement of the necessary technologies, the use of UA for object manipulation and cargo transport is becoming a more and more relevant research area. A reliable identification and localization of cargo and interaction objects as well as maintaining the required flight precision are essential to guarantee a successful object handling. Within this paper we demonstrate the successful application of an autonomous UA equipped with a lightweight suction gripper for object interaction. We discuss the approach used for precise localization as well as the identification and pose estimation of individual gripping objects. Concluding, the overall system performance is evaluated within an industrial-oriented use case.
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