A husband and wife have died after being trapped in a private sauna room that caught fire in Japan on Monday. Tokyo police are investigating whether a faulty doorknob trapped the couple inside the room at Sauna Tiger, in the city's Akasaka district, local media has reported. Investigators also found that the facility's emergency alarm system was switched off, and allegedly had been for two years. We offer our deepest condolences... and our heartfelt sympathies for the deep grief and pain that cannot be expressed in words, Sauna Tiger said in a statement on its website. The victims have been named by local media as Yoko Matsuda, a 37-year-old nail artist, and her husband Masanari, 36, who ran a beauty salon.

Reinforcement Learning (RL) has brought forth ideas of autonomous robots that can navigate real-world environments with ease, aiding humans in a variety of tasks. RL agents have just begun to make their way out of simulation into the real world. Once in the real world, benchmark tasks often fail to transfer into useful skills. We introduce DoorGym, a simulation environment intended to be the first step to move RL from toy environments towards useful atomic skills that can be composed and extended towards a broader goal. DoorGym is an open-source door simulation framework designed to be highly configurable. We also provide a baseline PPO (Proximal Policy Optimization) and SAC (Soft Actor-Critic)implementation, which achieves a success rate of up to 70% for common tasks in this environment. Environment kit available here:https://github.com/PSVL/DoorGym/

Robots can walk, talk, run a hotel … and are entirely stumped by a doorknob. Sure, the SpotMini, a doglike domestic helper from Boston Dynamics, can climb stairs, but it struggles to reliably hand over a can of soda. That's why some roboticists think the field needs to flip its perspective. "There are two approaches to building robots," says Maya Cakmak, a researcher at the University of Washington. "Make the robot more humanlike to handle the environment, or design the environment to make it a better fit for the robot."