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In this paper we present our hardware design and control approaches for amobile manipulation platform used in Challenge 2 of the MBZIRC 2020competition. In this challenge, a team of UAVs and a single UGV collaborate inan autonomous, wall-building scenario, motivated by construction automation andlarge-scale robotic 3D printing. The robots must be able, autonomously, todetect, manipulate, and transport bricks in an unstructured, outdoorenvironment. Our control approach is based on a state machine that dictateswhich controllers are active at each stage of the Challenge. In the first stageour UGV uses visual servoing and local controllers to approach the targetobject without considering its orientation. The second stage consists ofdetecting the object's global pose using OpenCV-based processing of RGB-D imageand point-cloud data, and calculating an alignment goal within a global map.The map is built with Google Cartographer and is based on onboard LIDAR, IMU,and GPS data. Motion control in the second stage is realized using the ROS MoveBase package with Time-Elastic Band trajectory optimization. Visual servoalgorithms guide the vehicle in local object-approach movement and the arm inmanipulating bricks. To ensure a stable grasp of the brick's magnetic patch, wedeveloped a passively-compliant, electromagnetic gripper with tactile feedback.Our fully-autonomous UGV performed well in Challenge 2 and in post-competitionevaluations of its brick pick-and-place algorithms.

Autonomous, Mobile Manipulation in a Wall-building Scenario: Team LARICS at MBZIRC 2020