4 accepted papers
We address real-time obstacle avoidance for redundant manipulators where tracking and safety constraints can conflict and render quadratic programs (QPs) infeasible. We propose AVO-QP, a sensor-guided velocity-level planner that fuses RGB-D depth with learned detection to maintain situational awaren
In unknown environments, navigating a robot by a given image to a specific location or instance is critical and challenging. The existing end-to-end approaches require simultaneous implicit learning of multiple subtasks, and modular approaches depend on metric information. Both approaches face high
This paper proposes a sensitivity analysis framework based on set-valued mapping for deep neural networks (DNN) to understand and compute how the solutions (model weights) of DNN respond to perturbations in the training data. As a DNN may not exhibit a unique solution (minima) and the algorithm of s…
Person search is a widely-concerned computer vision task that aims to jointly solve the problems of pedestrian detection and person re-identification in panoramic scenes. However, the pedestrian detection focuses on the consistency of pedestrians, while the person re-identification attempts to extra…