30 citations · 50 across the 8 of their papers we have counts for
8 papers
Performance comparison of tethered and self-propelled models of fish locomotion using unsteady thin airfoil theory
Anshul Nayak, Emad Masroor, Hodjat Pendar
Numerous experimental and computational studies have been conducted in the past few decades to understand the swimming performance of fish, and to identify the optimal kinematic st…
Belief-Aware VLM Model for Human-like Reasoning
Anshul Nayak, Shahil Shaik, Yue Wang
Traditional neural network models for intent inference rely heavily on observable states and struggle to generalize across diverse tasks and dynamic environments. Recent advances i…
MA-VLCM: A Vision Language Critic Model for Value Estimation of Policies in Multi-Agent Team Settings
Shahil Shaik, Aditya Parameshwaran, Anshul Nayak +2
Multi-agent reinforcement learning (MARL) commonly relies on a centralized critic to estimate the value function. However, learning such a critic from scratch is highly sample-inef…
Prediction uncertainty-aware planning using deep ensembles and trajectory optimisation
Anshul Nayak, Azim Eskandarian
Human motion is stochastic and ensuring safe robot navigation in a pedestrian-rich environment requires proactive decision-making. Past research relied on incorporating determinist…
Cooperative Probabilistic Trajectory Forecasting under Occlusion
Anshul Nayak, Azim Eskandarian
Perception and planning under occlusion is essential for safety-critical tasks. Occlusion-aware planning often requires communicating the information of the occluded object to the…
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty
Anshul Nayak, Azim Eskandarian, Zachary Doerzaph +1
One of the fundamental challenges in the prediction of dynamic agents is robustness. Usually, most predictions are deterministic estimates of future states which are over-confident…
X-CAR: An Experimental Vehicle Platform for Connected Autonomy Research Powered by CARMA
Goodarz Mehr, Prasenjit Ghorai, Ce Zhang +4
Autonomous vehicles promise a future with a safer, cleaner, more efficient, and more reliable transportation system. However, the current approach to autonomy has focused on buildi…
Uncertainty estimation of pedestrian future trajectory using Bayesian approximation
Anshul Nayak, Azim Eskandarian, Zachary Doerzaph
Past research on pedestrian trajectory forecasting mainly focused on deterministic predictions which provide only point estimates of future states. These future estimates can help…