all AI news
RAP: Risk-Aware Prediction for Robust Planning. (arXiv:2210.01368v1 [cs.LG])
Oct. 5, 2022, 1:11 a.m. | Haruki Nishimura, Jean Mercat, Blake Wulfe, Rowan McAllister, Adrien Gaidon
cs.LG updates on arXiv.org arxiv.org
Robust planning in interactive scenarios requires predicting the uncertain
future to make risk-aware decisions. Unfortunately, due to long-tail
safety-critical events, the risk is often under-estimated by finite-sampling
approximations of probabilistic motion forecasts. This can lead to
overconfident and unsafe robot behavior, even with robust planners. Instead of
assuming full prediction coverage that robust planners require, we propose to
make prediction itself risk-aware. We introduce a new prediction objective to
learn a risk-biased distribution over trajectories, so that risk evaluation
simplifies …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US
Research Engineer
@ Allora Labs | Remote
Ecosystem Manager
@ Allora Labs | Remote
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US