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20242026
most citedToward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunities

1 citations · 1 across the 5 of their papers we have counts for

collaborators

9 papers

cs.RO2026

Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations

Zhiyuan Zhang, Adeesh Desai, Jyun-Chi Hu +7

Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenanc…

cs.RO2026

ContactWorld: What Matters in Vision-Tactile World Models for Contact-Rich Manipulation

Zhiyuan Zhang, Pokuang Zhou, Kaidi Zhang +6

Contact-rich manipulation requires world models to reason over complex contact dynamics from multimodal sensory observations. However, it remains unclear which representation prope…

cs.RO2026

Flow Motion Policy: Manipulator Motion Planning with Flow Matching Models

Davood Soleymanzadeh, Xiao Liang, Minghui Zheng

Open-loop end-to-end neural motion planners have recently been proposed to improve motion planning for robotic manipulators. These methods enable planning directly from sensor obse…

cs.RO20261 cited

Toward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunities

Davood Soleymanzadeh, Ivan Lopez-Sanchez, Hao Su +3

State-of-the-art generalist manipulation policies have enabled the deployment of robotic manipulators in unstructured human environments. However, these frameworks struggle in clut…

cs.RO2026

GAIDE: Graph-based Attention Masking for Spatial- and Embodiment-aware Motion Planning

Davood Soleymanzadeh, Xiao Liang, Minghui Zheng

Sampling-based motion planning algorithms are widely used for motion planning of robotic manipulators, but they often struggle with sample inefficiency in high-dimensional configur…

eess.SY2026

Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World

Joonkyung Kim, Wenxi Chen, Davood Soleymanzadeh +9

The integration of foundation models (FMs) into robotics has accelerated real-world deployment, while introducing new safety challenges arising from open-ended semantic reasoning a…