Category: Blog

By Abrar Anwar Robots are increasingly expected to perceive and interact with their environments over extended periods. Robots are deployed for hours, if not days, at a time and they incidentally perceive different objects, events, and locations. For robots to understand and respond to questions that require complex multi-step reasoning in scenarios where the robot has … Continue reading ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation

By Ishika Singh Everyday household tasks require both common sense understanding of the world and situated knowledge about the current environment. To create a task plan for “Make dinner” an agent needs common sense: object affordances, such as the stove can be used to make food; logical sequences of actions, such as the oven must be preheated … Continue reading Language Models meet Classical Planners to make smarter Robot Task Plans

Quality Diversity algorithms identify many diverse solutions to solve problems rather than a single best option. Researchers developed pyribs to facilitate development of research projects that use Quality Diversity. Continue reading pyribs: Accelerating Quality Diversity Research

Large language models can help our robots adapt to new tasks and situations by enabling better pre-training and by guiding them in unfamiliar settings. Continue reading LLMs can help robots learn new tasks in unfamiliar places