CoFreeVLA reduces dual-arm self-collision rates from 0.54 to 0.23 and improves task success rates to 0.61 using a Vision-Language-Action model with risk estimation.

Yaohua Liu, Binkai Ou, Hengjun Zhang

Dual-Stance Cooperative Debate (DSCD-Nav) enhances object navigation via multi-round evidence cross-checking, boosting success rate by 20% on HM3Dv2.

Weitao An, Qi Liu, Chenghao Xu et al.

DeFM employs self-supervised pretraining on 60M depth images, learning geometric and semantic features for robotic tasks with state-of-the-art results.

Manthan Patel, Jonas Frey, Mayank Mittal et al.

Point Bridge leverages unified point cloud representations for zero-shot sim-to-real transfer, achieving up to 44% performance gains.

Siddhant Haldar, Lars Johannsmeier, Lerrel Pinto et al.

HumanoidPF encodes humanoid-obstacle relationships, enabling collision-free navigation in cluttered indoor scenes with success rate over 93%.

Han Xue, Sikai Liang, Zhikai Zhang et al.

MonoRace employs monocular camera and IMU for champion-level drone racing at speeds up to 100 km/h without external tracking.

Stavrow A. Bahnam, Robin Ferede, Till M. Blaha et al.

TIDAL decouples semantic reasoning and high-frequency control via dual-frequency architecture, achieving 9Hz updates and 2x performance improvement in dynamic tasks.

Yuteng Sun, Haoran Wang, Ruofei Bai et al.

PALM employs structured affordance prediction and progress estimation with diffusion models, achieving 91.8% success in long-horizon robotic tasks.

Yuanzhe Liu, Jingyuan Zhu, Yuchen Mo et al.

Commercial FMCW millimeter-wave radar achieves sub-centimeter water level accuracy with minimal calibration, enabling autonomous monitoring.

Anna Zavei-Boroda, J. Toby Minear, Kyle Harlow et al.

LOST-3DSG employs low-dimensional word embeddings for lightweight open-vocabulary 3D scene graphs, enabling efficient dynamic object tracking.

Sara Micol Ferraina, Michele Brienza, Francesco Argenziano et al.

Multi-source diverse pretraining enables human-to-robot skill transfer via vision-language-action models, nearly doubling generalization performance.

Simar Kareer, Karl Pertsch, James Darpinian et al.

LookPlanGraph uses VLM graph augmentation for instruction following in dynamic environments, improving task success rates.

Anatoly O. Onishchenko, Alexey K. Kovalev, Aleksandr I. Panov

Fusion of YOLO-based gate detection and Kalman filter drift correction enhances monocular VIO for drone racing, achieving speeds over 59 km/h.

Maulana Bisyir Azhari, Donghun Han, Je In You et al.

Mimic-video combines pretrained video models with inverse dynamics decoders, achieving 10x sample efficiency and 2x faster convergence in robotic control tasks.

Jonas Pai, Liam Achenbach, Victoriano Montesinos et al.

RoboTracer employs 3D-aware VLM with reinforcement fine-tuning, achieving 79.1% success in spatial reasoning tasks.

Enshen Zhou, Yibo Li, Jingkun An et al.

A YOLO–TensorRT–Isaac ROS QuadPlane landing stack achieved 32.7 ms per frame, enabling over 30 FPS edge inference.

Ashik E Rasul, Humaira Tasnim, Ji Yu Kim et al.

AEGIS integrates control barrier functions into VLA models, achieving over 50% improvement in obstacle avoidance and nearly 10% higher task success.

Songqiao Hu, Zeyi Liu, Shuang Liu et al.

ResponsibleRobotBench evaluates robot responsibility in risk environments using multimodal LLMs with 85% success rate.

Lei Zhang, Ju Dong, Kaixin Bai et al.

DiskChunGS achieves large-scale 3D Gaussian SLAM via chunk-based memory management, completing all KITTI sequences successfully.

Casimir Feldmann, Maximum Wilder-Smith, Vaishakh Patil et al.

DLR framework uses information-theoretic pattern discovery to generate diverse, high-success trajectories for VLA pretraining, improving downstream generalization.

Rushuai Yang, Zhiyuan Feng, Tianxiang Zhang et al.