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Shiqing Wei

4 accepted papers

2026

A Differentiable Distance Metric for Robotics Through Generalized Alternating Projection

Vinicius Mariano Gonçalves, Shiqing Wei, Eduardo Malacarne S. de Souza, Prashanth Krishnamurthy, Anthony Tzes, Farshad Khorrami
RA-L 2026

In many robotics applications, it is necessary to compute not only the distance between the robot and the environment, but also its derivative - for example, when using control barrier functions. However, since the traditional Euclidean distance is not differentiable, meaning it is not guaranteed to

Cited by 0Source ↗Scholar ↗
2026

A Differentiable Distance Metric for Robotics through Generalized Alternating Projection

Vinicius Mariano Gonçalves, Shiqing Wei, Eduardo Malacarne Soeiro de Souza, Prashanth Krishnamurthy, Anthony Tzes, Farshad Khorrami
ICRA 2026poster

In many robotics applications, it is necessary to compute not only the distance between the robot and the environment, but also its derivative - for example, when using control barrier functions. However, since the traditional Euclidean distance is not differentiable, meaning it is not guaranteed to…

Cited by 0Source ↗PDF ↗Scholar ↗
2024

DiffOcclusion: Differentiable Optimization Based Control Barrier Functions for Occlusion-Free Visual Servoing

Shiqing Wei, Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy, Farshad Khorrami
RA-L 2024

The visibility (possibly partial) of some image features is crucial to a broad class of visual servoing-based control. In this letter, we consider the setting of image-based visual servoing (IBVS) and address the fundamental problem of keeping a moving object with an unknown motion profile in the fi

Cited by 21Source ↗Scholar ↗
2022

E2EC: An End-to-End Contour-Based Method for High-Quality High-Speed Instance Segmentation

Tao Zhang, Shiqing Wei, Shunping Ji
CVPR 2022poster

Contour-based instance segmentation methods have developed rapidly recently but feature rough and handcrafted front-end contour initialization, which restricts the model performance, and an empirical and fixed backend predicted-label vertex pairing, which contributes to the learning difficulty. In t…

Cited by 113PDF ↗code ↗Scholar ↗