Zobrazeno 1 - 10
of 1 376
pro vyhledávání: '"Lozano-Pérez AS"'
We present a novel approach, MAGIC (manipulation analogies for generalizable intelligent contacts), for one-shot learning of manipulation strategies with fast and extensive generalization to novel objects. By leveraging a reference action trajectory,
Externí odkaz:
http://arxiv.org/abs/2411.09627
Careful robot manipulation in every-day cluttered environments requires an accurate understanding of the 3D scene, in order to grasp and place objects stably and reliably and to avoid mistakenly colliding with other objects. In general, we must const
Externí odkaz:
http://arxiv.org/abs/2410.23643
Autor:
Fang, Xiaolin, Huang, Bo-Ruei, Mao, Jiayuan, Shone, Jasmine, Tenenbaum, Joshua B., Lozano-Pérez, Tomás, Kaelbling, Leslie Pack
Generalization to novel object configurations and instances across diverse tasks and environments is a critical challenge in robotics. Keypoint-based representations have been proven effective as a succinct representation for capturing essential obje
Externí odkaz:
http://arxiv.org/abs/2410.23254
Manipulation of large objects over long horizons (such as carts in a warehouse) is an essential skill for deployable robotic systems. Large objects require mobile manipulation which involves simultaneous manipulation, navigation, and movement with th
Externí odkaz:
http://arxiv.org/abs/2410.06911
Vision-Language Models (VLM) can generate plausible high-level plans when prompted with a goal, the context, an image of the scene, and any planning constraints. However, there is no guarantee that the predicted actions are geometrically and kinemati
Externí odkaz:
http://arxiv.org/abs/2410.02193
The real world is unpredictable. Therefore, to solve long-horizon decision-making problems with autonomous robots, we must construct agents that are capable of adapting to changes in the environment during deployment. Model-based planning approaches
Externí odkaz:
http://arxiv.org/abs/2409.19226
The problem of mating two parts with low clearance remains difficult for autonomous robots. We present bi-level belief assembly (BILBA), a model-based planner that computes a sequence of compliant motions which can leverage contact with the environme
Externí odkaz:
http://arxiv.org/abs/2409.15774
We introduce uncertainty-aware object instance segmentation (UncOS) and demonstrate its usefulness for embodied interactive segmentation. To deal with uncertainty in robot perception, we propose a method for generating a hypothesis distribution of ob
Externí odkaz:
http://arxiv.org/abs/2408.04760
When using sampling-based motion planners, such as PRMs, in configuration spaces, it is difficult to determine how many samples are required for the PRM to find a solution consistently. This is relevant in Task and Motion Planning (TAMP), where many
Externí odkaz:
http://arxiv.org/abs/2407.17394
Recent developments in pretrained large language models (LLMs) applied to robotics have demonstrated their capacity for sequencing a set of discrete skills to achieve open-ended goals in simple robotic tasks. In this paper, we examine the topic of LL
Externí odkaz:
http://arxiv.org/abs/2406.05572