5 papers
AeroGrab: A Unified Framework for Aerial Grasping in Cluttered Environments
Shivansh Pratap Singh, Naveen Sudheer Nair, Samaksh Ujjawal +4
Reliable aerial grasping in cluttered environments remains challenging due to occlusions and collision risks. Existing aerial manipulation pipelines largely rely on centroid-based…
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…
Reinforcement Learning with Inner-loop Dynamics Estimator for Aerial Manipulation under Uncertainty
Shivansh Pratap Singh, Samaksh Ujjwal, Ishita Chaudhary +3
Aerial manipulators enable physical interaction in hard-to-reach environments; however, the combined problem of direct whole-body aerial manipulation under rapid arm motion, payloa…
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…
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…