Reactive Semantic Planning in Unexplored Semantic Environments Using Deep Perceptual Feedback
| Autor: | Daniel E. Koditschek, Georgios Pavlakos, J. Diego Caporale, Vasileios Vasilopoulos, Kostas Daniilidis, Sean L. Bowman, George J. Pappas |
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| Rok vydání: | 2020 |
| Předmět: |
Control and Optimization
Computer science Mechanical Engineering media_common.quotation_subject 05 social sciences Biomedical Engineering Probabilistic logic Reactive planning 050105 experimental psychology Object detection Computer Science Applications Human-Computer Interaction 03 medical and health sciences 0302 clinical medicine Artificial Intelligence Control and Systems Engineering Perceptual learning Human–computer interaction Perception 0501 psychology and cognitive sciences Computer Vision and Pattern Recognition Representation (mathematics) 030217 neurology & neurosurgery media_common Gesture |
| Zdroj: | IEEE Robotics and Automation Letters. 5:4455-4462 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2020.3001496 |
| Popis: | This letter presents a reactive planning system that enriches the topological representation of an environment with a tightly integrated semantic representation, achieved by incorporating and exploiting advances in deep perceptual learning and probabilistic semantic reasoning. Our architecture combines object detection with semantic SLAM, affording robust, reactive logical as well as geometric planning in unexplored environments. Moreover, by incorporating a human mesh estimation algorithm, our system is capable of reacting and responding in real time to semantically labeled human motions and gestures. New formal results allow tracking of suitably non-adversarial moving targets, while maintaining the same collision avoidance guarantees. We suggest the empirical utility of the proposed control architecture with a numerical study including comparisons with a state-of-the-art dynamic replanning algorithm, and physical implementation on both a wheeled and legged platform in different settings with both geometric and semantic goals. |
| Databáze: | OpenAIRE |
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