Dynamic PDE-based ergodic exploration improves search efficiency for drifting targets in flow fields, achieving 50% higher detection rates.

Luka Lanča, Karlo Jakac, Sylvain Calinon et al.

SeqMultiGrasp system uses diffusion model for multi-object grasping with dexterous hand, achieving 65.8% success in simulation.

Sicheng He, Zeyu Shangguan, Kuanning Wang et al.

Proposes CycleVAE and causal Transformer for unsupervised cross-embodiment robotic manipulation, generating smooth trajectories with 85% success rate.

Apan Dastider, Hao Fang, Mingjie Lin

RoboCopilot system enhances robot bimanual manipulation skills via interactive imitation learning, showing performance improvement in experiments.

Philipp Wu, Yide Shentu, Qiayuan Liao et al.

PointVLA selectively injects 3D point cloud features into frozen pre-trained VLA models, boosting multi-task and spatial reasoning performance.

Chengmeng Li, Junjie Wen, Yan Peng et al.

SafePlan combines formal logic and chain-of-thought reasoning, reducing harmful prompt acceptance by 90.5% in robotic task planning.

Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang et al.

CompDiffuser leverages bidirectional diffusion models for compositional long-horizon trajectory stitching, outperforming existing methods.

Yunhao Luo, Utkarsh A. Mishra, Yilun Du et al.

GAGrasp employs geometric algebra with diffusion and physics-based refinement to enhance SE(3) equivariance, improving dexterous grasp generation robustness and efficiency.

Tao Zhong, Christine Allen-Blanchette

PD-VLA employs parallel fixed-point iteration to accelerate action chunking in VLA models, achieving 2.52× speedup while maintaining performance.

Wenxuan Song, Jiayi Chen, Pengxiang Ding et al.

Phantom method trains robots using human videos, achieving 92% success without robot data.

Marion Lepert, Jiaying Fang, Jeannette Bohg

Falcon reuses partial denoising actions based on historical data, achieving 2-7x speedup with negligible performance loss in diffusion policies.

Haojun Chen, Minghao Liu, Chengdong Ma et al.

DexGraspVLA achieves over 90% success in dexterous grasping in complex scenes.

Yifan Zhong, Xuchuan Huang, Ruochong Li et al.

Utilizing synthetic data and virtual simulation to identify and generate corner cases for enhanced autonomous vehicle safety.

Gabriel Kenji Godoy Shimanuki, Alexandre Moreira Nascimento, Lucio Flavio Vismari et al.

Point Policy unifies observations and actions via key points, learning robot policies solely from offline human videos, achieving 75% performance boost.

Siddhant Haldar, Lerrel Pinto

GazeBot integrates gaze information and motion bottlenecks with Transformer-based prediction to enhance skill generalization in robot manipulation, achieving success rates over 85% in unseen scenarios.

Ryo Takizawa, Izumi Karino, Koki Nakagawa et al.

Proposes a convex-structured joint estimation method for states and noise covariance, with analytical solutions, applied to SLAM and robotics.

Kasra Khosoussi, Iman Shames

DGPPO combines discrete graph CBFs with RL to achieve safe, high-performance multi-agent control under unknown discrete dynamics.

Songyuan Zhang, Oswin So, Mitchell Black et al.

ConditionNET uses vision-language transformers to learn action preconditions and effects, boosting real-time robot execution monitoring.

Daniel Sliwowski, Dongheui Lee

Introduces the GO multimodal dataset with six sensors, supporting perception and navigation in unstructured outdoor environments.

Peng Jiang, Kasi Viswanath, Akhil Nagariya et al.

Proposed a dynamic model identification-based gravity compensation for dVRK-Si PSM, constructing a full kinematic model with improved control accuracy.

Haoying Zhou, Hao Yang, Anton Deguet et al.