arXiv:2606. 27624v1 Announce Type: cross Abstract: Using robots to estimate the location of the radiation source is an effective way to improve efficiency and safety.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.
arXiv:2608. 09166v1 Announce Type: cross Abstract: Reliable uncertainty representation is essential for deploying autonomous systems that interact with their environment, as robots must reason about how uncertainty arising from both stochasticity and model mismatch is impacted by contacts with obstacles (e.
arXiv:2606. 14763v1 Announce Type: cross Abstract: Real-time autonomous navigation in dynamic, unknown environments remains a fundamental challenge for mobile robotics.
arXiv:2606. 19729v2 Announce Type: replace-cross Abstract: Planning under uncertainty is an essential capability for autonomous robots.
arXiv:2606. 19729v1 Announce Type: cross Abstract: Planning under uncertainty is an essential capability for autonomous robots.
arXiv:2608. 05588v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires repeatedly planning collision-free paths for agents that continuously receive new goals upon reaching their current ones.
arXiv:2607. 12784v1 Announce Type: cross Abstract: Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation.