1 citations · 1 across the 11 of their papers we have counts for
11 papers
A Switched Adaptive Control Framework for Aerial Manipulators Under Dynamic Transitions
Rishabh Dev Yadav, Saksham Gupta, Amitabh Sharma +4
Aerial manipulators represent the forefront of aerial robotics. Although potentially capable of complex interaction tasks, controlling aerial manipulators throughout the dynamic tr…
Physics-Aware Sparse Learning and Selective Online Adaptation for Euler-Lagrange Robot Dynamics
Rishabh Dev Yadav, Samaksh Ujjawal, Sihao Sun +2
Accurate dynamics models are essential for model-based robotic control, yet nominal Euler--Lagrange models often become inaccurate in the presence of payload variation, unmodeled c…
Adaptive Artificial Time-Delay Control with Barrier Lyapunov Constraints for Euler-Lagrange Robots
Saksham Gupta, Rishabh Dev Yadav, Sarthak Mishra +5
This paper addresses the challenge of simultaneously compensating for state-dependent uncertainties and enforcing time-varying state constraints in Euler-Lagrange systems, a common…
Learning Cross-Coupled and Regime Dependent Dynamics for Aerial Manipulation
Rishabh Dev Yadav, Samaksh Ujjawal, Shivansh Pratap Singh +4
Accurate dynamics modeling of aerial manipulators is challenging because platform--manipulator coupling, history-dependent interactions, and changing payload or manipulator configu…
Learn Structure, Adapt on the Fly: Multi-Scale Residual Learning and Online Adaptation for Aerial Manipulators
Samaksh Ujjawal, Naveen Sudheer Nair, Shivansh Pratap Singh +3
Autonomous Aerial Manipulators (AAMs) are inherently coupled, nonlinear systems that exhibit nonstationary and multiscale residual dynamics, particularly during manipulator reconfi…
ARCADE: Adaptive Robot Control with Online Changepoint-Aware Bayesian Dynamics Learning
Rishabh Dev Yadav, Avirup Das, Hongyu Song +2
Real-world robots must operate under evolving dynamics caused by changing operating conditions, external disturbances, and unmodeled effects. These may appear as gradual drifts, tr…
AERMANI-Diffusion: Regime-Conditioned Diffusion for Dynamics Learning in Aerial Manipulators
Samaksh Ujjawal, Shivansh Pratap Singh, Naveen Sudheer Nair +3
Aerial manipulators undergo rapid, configuration-dependent changes in inertial coupling forces and aerodynamic forces, making accurate dynamics modeling a core challenge for reliab…
AERMANI-VLM: Structured Prompting and Reasoning for Aerial Manipulation with Vision Language Models
Sarthak Mishra, Rishabh Dev Yadav, Avirup Das +3
The rapid progress of vision--language models (VLMs) has sparked growing interest in robotic control, where natural language can express the operation goals while visual feedback l…
SoraNav: Adaptive UAV Task-Centric Navigation via Zeroshot VLM Reasoning
Hongyu Song, Rishabh Dev Yadav, Cheng Guo +1
Autonomous navigation under natural language instructions represents a crucial step toward embodied intelligence, enabling complex task execution in environments ranging from indus…
Impedance and Stability Targeted Adaptation for Aerial Manipulator with Unknown Coupling Dynamics
Amitabh Sharma, Saksham Gupta, Shivansh Pratap Singh +5
Stable aerial manipulation during dynamic tasks such as object catching, perching, or contact with rigid surfaces necessarily requires compliant behavior, which is often achieved v…
Safe Distributed Learning-Enhanced Predictive Control for Multiple Quadrupedal Robots
Weishu Zhan, Zheng Liang, Hongyu Song +1
Quadrupedal robots exhibit remarkable adaptability in unstructured environments, making them well-suited for formation control in real-world applications. However, keeping stable f…