Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequences. A robot may safely brush against a cardboard box while even minor contact with a glass, laptop, or unstable object may be undesirable. Moreover, a direct robot--obje...
Imagine-TAMP is introduced, an interleaved planning and execution framework that uses semantic and geometric imagination to compare alternative task-level strategies under partial observability before committing to expensive motion planning and experiments show that imagination-guided evaluation improves observation-ve...
Antareep Singha, Shiv Kumar, Yoonwoo Kim et al.· 0 citations
BEV-IMTP is presented, a lightweight instance mapping and trajectory prediction network designed for Bird's-Eye-View representations that achieves a 4.6% improvement in semantic map mIoU and a 1.8% gain in instance motion mIoU compared to state-of-the-art methods.
N. Harivinod, S. Abhilash, M. Muneshwara et al.· Discover Artificial Intellig...· 0 citations
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