Study uses police-reported data to benchmark ADS crash rates, addressing data selection and reporting bias issues.

John M. Scanlon, Kristofer D. Kusano, Laura A. Fraade-Blanar et al.

Waymo ADS achieved an 80% lower crash rate (0.6 IPMM) than human benchmarks (2.80 IPMM) over 7.14M miles, demonstrating significant safety improvements.

Kristofer D. Kusano, John M. Scanlon, Yin-Hsiu Chen et al.

Hierarchical active inference model integrating visual perception and planning for autonomous navigation.

Daria de Tinguy, Toon van de Maele, Tim Verbelen et al.

Unified definition and hierarchical taxonomy of transfer learning in robotics, analyzing applications across robot, task, and environment dimensions with specific algorithms and datasets.

Noémie Jaquier, Michael C. Welle, Andrej Gams et al.

Survey on LLMs in robotics, enhancing control, perception, and decision-making.

Fanlong Zeng, Wensheng Gan, Zezheng Huai et al.

A demonstration-free hierarchical planning method using EMD-space planning for zero-shot deformable manipulation.

Yang You, Bokui Shen, Congyue Deng et al.

RoboGen uses generative models to automatically create diverse tasks and environments, enhancing robotic skill learning efficiency.

Yufei Wang, Zhou Xian, Feng Chen et al.

RoboFlamingo leverages open-source VLMs for robot control, achieving 96.4% success rate, outperforming SOTA by a large margin.

Xinghang Li, Minghuan Liu, Hanbo Zhang et al.

nvblox leverages GPU acceleration for incremental Signed Distance Field (SDF) mapping, achieving 177× faster surface reconstruction and 31× faster distance field computation, significantly enhancing robotic path planning.

Alexander Millane, Helen Oleynikova, Emilie Wirbel et al.

Utilizes multimodal foundation models with transformer-based patch features for open-set end-to-end autonomous driving, boosting robustness and interpretability.

Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao et al.

MimicTouch leverages multi-modal tactile demonstrations, low-dimensional representation, non-parametric imitation, and residual RL to improve contact-rich manipulation success to 96%.

Kelin Yu, Yunhai Han, Qixian Wang et al.

navlie is a Python package supporting on-manifold state estimation algorithms (EKF, invariant EKF, sigma-point filters) on Lie groups, enabling rapid prototyping.

Charles Champagne Cossette, Mitchell Cohen, Vassili Korotkine et al.

DACOOP-A integrates attention mechanisms and artificial potential fields, boosting multi-robot pursuit success to 57% in simulations.

Zheng Zhang, Dengyu Zhang, Qingrui Zhang et al.

DIP-3D integrates sparse stereo triangulation and pose estimation to locate diver-pointed objects in 3D, improving multi-object discrimination in underwater scenes.

Chelsey Edge, Demetrious Kutzke, Megdalia Bromhal et al.

AcTExplore employs reinforcement learning for active tactile exploration, achieving 95.97% IoU coverage on unseen objects with limited steps.

Amir-Hossein Shahidzadeh, Seong Jong Yoo, Pavan Mantripragada et al.

Introduces ORION framework leveraging GPT-4 for open-world personalized robot navigation, significantly improving success rates with multi-feedback natural language interaction.

Yinpei Dai, Run Peng, Sikai Li et al.

ConceptGraphs combines multi-view geometric fusion and large vision-language models to build open-vocabulary 3D scene graphs for robot perception and planning.

Qiao Gu, Alihusein Kuwajerwala, Sacha Morin et al.

PolarNet leverages 3D point clouds and multimodal transformers for language-guided robotic manipulation, outperforming 2D methods with 92.1% success in single-task and 60% on real robots.

Shizhe Chen, Ricardo Garcia, Cordelia Schmid et al.

Combining ANN with RevDE outperforms CPG and DRL in modular robot gait learning, achieving higher speed and robustness.

Jie Luo, Jakub Tomczak, Karine Miras et al.

GELLO uses low-cost 3D-printed kinematic replicas for intuitive robot teleoperation, improving demonstration efficiency.

Philipp Wu, Yide Shentu, Zhongke Yi et al.