2 citations · 2 across the 11 of their papers we have counts for
12 papers
Occlusion-Aware, Quasi-Static, Stability-Oriented Trajectory Planning on Uneven Terrain
Amith Manoharan, Chinmay Mundane, Aayush Bahukhandi +3
Autonomous navigation in unstructured off-road environments requires reasoning about both vehicle--terrain interaction and environmental unknowns. We propose a model-based framewor…
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…
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…
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…
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…
ATPPNet: Attention based Temporal Point cloud Prediction Network
Kaustab Pal, Aditya Sharma, Avinash Sharma +1
Point cloud prediction is an important yet challenging task in the field of autonomous driving. The goal is to predict future point cloud sequences that maintain object structures…
NeuroSMPC: A Neural Network guided Sampling Based MPC for On-Road Autonomous Driving
Kaustab Pal, Aditya Sharma, Mohd Omama +2
In this paper we show an effective means of integrating data driven frameworks to sampling based optimal control to vastly reduce the compute time for easy adoption and adaptation…
Hilbert Space Embedding-based Trajectory Optimization for Multi-Modal Uncertain Obstacle Trajectory Prediction
Basant Sharma, Aditya Sharma, K. Madhava Krishna +1
Safe autonomous driving critically depends on how well the ego-vehicle can predict the trajectories of neighboring vehicles. To this end, several trajectory prediction algorithms h…
Multi-Modal Model Predictive Control through Batch Non-Holonomic Trajectory Optimization: Application to Highway Driving
Vivek K. Adajania, Aditya Sharma, Anish Gupta +3
Standard Model Predictive Control (MPC) or trajectory optimization approaches perform only a local search to solve a complex non-convex optimization problem. As a result, they cann…
Fast Adaptation of Manipulator Trajectories to Task Perturbation By Differentiating through the Optimal Solution
Shashank Srikanth, Mithun Babu, Houman Masnavi +3
Joint space trajectory optimization under end-effector task constraints leads to a challenging non-convex problem. Thus, a real-time adaptation of prior computed trajectories to pe…
Model Predictive Control for Micro Aerial Vehicle Systems (MAV) Systems
Gautham Vasan, Arun Kumar Singh, Madhava Krishna
This paper presents a method for path-following for quadcopter trajectories in real time. Non-Linear Guidance Logic is used to find the intercepts of the subsequent destination. Tr…