5 citations · 8 across the 5 of their papers we have counts for
5 papers
SILICA: Repurposing Diffusion Priors for Joint Glass Segmentation and Depth Estimation
Tarun R, Anuj Verma, Laksh Nanwani +2
Standard depth sensors systematically fail on transparent surfaces, creating corrupted 3D maps and severe navigation hazards. While specialized hardware sensors can detect glass, t…
Crowd-FM: Learned Optimal Selection of Conditional Flow Matching-generated Trajectories for Crowd Navigation
Antareep Singha, Laksh Nanwani, Mathai Mathew P. +4
Safe and computationally efficient local planning for mobile robots in dense, unstructured human crowds remains a fundamental challenge. Moreover, ensuring that robot trajectories…
CrowdSurfer: Sampling Optimization Augmented with Vector-Quantized Variational AutoEncoder for Dense Crowd Navigation
Naman Kumar, Antareep Singha, Laksh Nanwani +6
Navigation amongst densely packed crowds remains a challenge for mobile robots. The complexity increases further if the environment layout changes, making the prior computed global…
Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIM
Laksh Nanwani, Kumaraditya Gupta, Aditya Mathur +3
Humans excel at forming mental maps of their surroundings, equipping them to understand object relationships and navigate based on language queries. Our previous work, SI Maps (Nan…
Instance-Level Semantic Maps for Vision Language Navigation
Laksh Nanwani, Anmol Agarwal, Kanishk Jain +7
Humans have a natural ability to perform semantic associations with the surrounding objects in the environment. This allows them to create a mental map of the environment, allowing…