2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.RO2026
LatentMimic: Terrain-Adaptive Locomotion via Latent Space Imitation
Zhiquan Wang, Yunyu Liu, Dipam Patel +3
Developing natural and diverse locomotion controllers for quadruped robots that can adapt to complex terrains while preserving motion style remains a significant challenge. Existin…
cs.AI2026
Neural Assistive Impulses: Synthesizing Exaggerated Motions for Physics-based Characters
Zhiquan Wang, Bedrich Benes
Physics-based character animation has become a fundamental approach for synthesizing realistic, physically plausible motions. While current data-driven deep reinforcement learning…
cs.AI2022★ 2 cited
Co-design of Embodied Neural Intelligence via Constrained Evolution
Zhiquan Wang, Bedrich Benes, Ahmed H. Qureshi +1
We introduce a novel co-design method for autonomous moving agents' shape attributes and locomotion by combining deep reinforcement learning and evolution with user control. Our ma…