5 papers
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…
MonoMPC: Monocular Vision Based Navigation with Learned Collision Model and Risk-Aware Model Predictive Control
Basant Sharma, Prajyot Jadhav, Pranjal Paul +2
Navigating unknown environments with a single RGB camera is challenging, as the lack of depth information prevents reliable collision-checking. While some methods use estimated dep…
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…
Swarm-Gen: Fast Generation of Diverse Feasible Swarm Behaviors
Simon Idoko, B. Bhanu Teja, K. Madhava Krishna +1
Coordination behavior in robot swarms is inherently multi-modal in nature. That is, there are numerous ways in which a swarm of robots can avoid inter-agent collisions and reach th…
Bi-level Trajectory Optimization on Uneven Terrains with Differentiable Wheel-Terrain Interaction Model
Amith Manoharan, Aditya Sharma, Himani Belsare +3
Navigation of wheeled vehicles on uneven terrain necessitates going beyond the 2D approaches for trajectory planning. Specifically, it is essential to incorporate the full 6dof var…