Abstract
With the development of quadruped robot technology, object tracking for quadruped robots has become an important research topic where violent camera shaking caused by the robot’s movement makes this task very challenging. In this letter, a quadruped robot object tracking dataset (QROD-111), including 111 video sequences, is first established, which was collected through our quadruped robot platform. A tracking algorithm based on Siamese network is then proposed where an alignment module is introduced to alleviate tracking difficulties caused by the quadruped robot movement. Moreover, a scale adaptation subnetwork is designed to alleviate the impact of the object scale variation during the whole tracking process. Experimental results demonstrate that our algorithm can achieve advanced performance for quadruped robot object tracking.
Published Version
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