SUMMARY In this paper, we present a novel passive single degree-of-freedom (DoF) manipulator design and its integration on an autonomous drone to capture a moving target. The end-effector is designed to be passive, to disengage the moving target from a flying UAV and capture it efficiently in the presence of disturbances, with minimal energy usage. It is also designed to handle target sway and the effect of downwash. The passive manipulator is integrated with the drone through a single DoF arm, and experiments are carried out in an outdoor environment. The rack-and-pinion mechanism incorporated for this manipulator ensures safety by extending the manipulator beyond the body of the drone to capture the target. The autonomous capturing experiments are conducted using a red ball hanging from a stationary drone and subsequently from a moving drone. The experiments show that the manipulator captures the target with a success rate of 70% even under environmental/measurement uncertainties and errors.

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This paper presents the design, development, and testing of hardware-software systems by the IISc-TCS team for Challenge 1 of the Mohamed Bin Zayed International Robotics Challenge 2020. The goal of Challenge 1 was to grab a ball suspended from a maneuvering UAV and pop balloons anchored to the ground, using suitable manipulators. The important tasks carried out to address this challenge include the design and development of a hardware system with efficient grabbing and popping mechanisms, considering the restrictions in volume and payload, design of accurate target interception algorithms using visual information suitable for outdoor environments, and development of a software architecture for dynamic, multi-agent, aerial systems performing complex tasks. In this paper, we discuss the design of a custom end-effector mounted on a single degree of freedom manipulator, and robust algorithms for the interception of targets in an uncertain environment. Vision-based guidance and tracking strategies are developed based on the concept of pursuit engagement and artificial potential function. The software architecture presented in this work develops an Operation Management System (OMS) architecture that allocates static and dynamic tasks collaboratively among multiple UAVs to perform any given task. An important aspect of this work is that all the systems developed were designed to operate in completely autonomous mode. A detailed description of the architecture along with simulations of complete challenge in the Gazebo environment and field experiment results are also included in this work. The developed hardware-software system is useful for counter-UAV systems and can be used for other applications.

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