Aravind Elanjimattathil Vijayan — accepted AI-conference papers

2025

Multi-critic Learning for Whole-body End-effector Twist Tracking

Aravind Elanjimattathil Vijayan, Andrei Cramariuc, Mattia Risiglione, Christian Gehring, Marco Hutter

CoRL 2025poster

Learning whole-body control for locomotion and arm motions in a single policy has challenges, as the two tasks have conflicting goals. For instance, efficient locomotion typically favors a horizontal base orientation, while end-effector tracking may benefit from base tilting to extend reachability.…

Cited by 0 Source ↗Scholar ↗

2020

Perceptive Locomotion in Rough Terrain - Online Foothold Optimization

Fabian Jenelten, Takahiro Miki, Aravind Elanjimattathil Vijayan, Marko Bjelonic, Marco Hutter

RA-L 2020

Compared to wheeled vehicles, legged systems have a vast potential to traverse challenging terrain. To exploit the full potential, it is crucial to tightly integrate terrain perception for foothold planning. We present a hierarchical locomotion planner together with a foothold optimizer that finds l

Cited by 105 Source ↗Scholar ↗

2018

Using Constrained Optimization for Real-Time Synchronization of Verbal and Nonverbal Robot Behavior

Aravind Elanjimattathil Vijayan, Simon Alexanderson, Jonas Beskow, Iolanda Leite

ICRA 2018poster

Most of the motion re-targeting techniques are grounded on virtual character animation research, which means that they typically assume that the target embodiment has unconstrained joint angular velocities. However, because robots often do have such constraints, traditional re-targeting approaches c…

Cited by 6 Source ↗Scholar ↗