Meet Casper👻, a friendly robot sidekick who shadows your day, decodes your intents on the fly, and lends a hand while you stay in control! . Instead of passively receiving commands, what if a robot actively sense what you need in the background, and step in when confident? (1/n)

Excited that Casper 👻 is accepted to CoRL 2025! #CoRL2025 A big thank you to all the collaborators :).

RT @siqi_shang: 3D print tactile sensors anywhere inside your fin-ray fingers! We present FORTE - a solution to sensorize compliant fingers….

RT @agiachris: What makes data “good” for robot learning? We argue: it’s the data that drives closed-loop policy success!. Introducing CUPI….

📢 Our #RSS2025 workshop on OOD generation in robotics is happening live now! . 📍EEB 132. Join us with a superb lineup of invited speakers and panelists: .@lschmidt3 @DorsaSadigh @andrea_bajcsy @HarryXu12 @MashaItkina @Majumdar_Ani @KarlPertsch.

RT @ArthurKZhang: Interested in deploying real robots in open-world, outdoor environments? Come to our presentation this Tuesday at 9:30AM,….

RT @DoubleHan07: Excited to present DOGlove at #RSS2025 today!.We’ve brought the glove with us, come by and try it out!.📌 Poster: All day a….

RT @arjun__gupta: How can we build mobile manipulation systems that generalize to novel objects and environments?. Come check out MOSART at….

RSS Pioneer poster happening live on grass @USC!! 😛😛come to Associate Park, poster #8 to chat more about continual robot learning, human-in-the-loop, and reliable deployment! #RSS2025

Workshop on Mobile Manipulation in #RSS2025 happening now!! Join us at Hughes Aircraft Electrical Engineering Center, Room 132 if you’re here in person, or join us on Zoom. Website:

RT @rkjenamani: Most assistive robots live in labs. We want to change that. FEAST enables care recipients to personalize mealtime assistan….

Checkout our paper and website for more details. A huge thank you to the team @rutavms @dafeijing Jack Pittenger @kiwi_sherbet @YuchenCui1 @ybisk @RobobertoMM @yukez !. @texas_robotics @UCLAComSci @CSDatCMU.

🔑Key insight from the user studies: VLM-based commonsense reasoning is crucial for diverse intent inference in real-world assistive tasks. Casper consistently outperforms the baselines on user workload and user satisfaction, as well as task performance metrics. (7/n)

🙋🏻‍♀️We conduct extensive user studies on multi-step mobile manipulation tasks. At each step, the robot disambiguates user intent among multiple plausible goals, selecting the correct one based on user inputs and visual context. (6/n)

Casper's key idea #2: Use a parameterized skill library to fulfill intents. Once confirmed by the user, Casper executes the corresponding skill with estimated parameters. (5/n)

Casper's key idea #1: Use VLM commonsense reasoning to infer diverse human intents. Casper generates task candidates from observations and infers intent from user inputs among the task candidates, repeating until predictions are self-consistent. (4/n)

Given user teleoperation input, Casper predicts user intent in real time. Upon user confirmation, it fulfills the intent with autonomous execution. Casper's background reasoning runs in parallel with foreground human control to minimize user disruption. (3/n)

📄paper: 🌐website: (2/n).

RT @ZEYULIU10: LLMs trained to memorize new facts can’t use those facts well.🤔. We apply a hypernetwork to ✏️edit✏️ the gradients for fact….