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X. Meng, P. Hou, and H. Li are with the Thrust of Robotics and Autonomous Systems, Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China. Z. Zhao and J. Civera are with the University of Zaragoza, Zaragoza, Spain. D. Cremers is with the School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. H. Wang is with the School of Automation and IntelligentSensing, Shanghai Jiao Tong University, Shanghai 200240, China (e-mail: wanghesheng @sjtu.edu.cn)
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Forget training monolithic policies: RoboRouter intelligently routes robotic manipulation tasks to the best off-the-shelf policy, boosting success rates by 13% in the real world.
By "dreaming" plausible scene completions, Dream-SLAM enables robots to navigate dynamic environments more effectively, achieving better localization, mapping, and exploration than existing methods.
Certifiably optimal solutions to 3D vision problems are now within reach, but choosing the right global solver (BnB, CR, or GNC) requires navigating a complex trade-off between optimality, robustness, and scalability.
