From the 4 of 110 papers with an AI index.
80 citations
- National University of SingaporeSG11 papers
- Zhejiang UniversityCN6 papers
- Centre for Quantum TechnologiesSG5 papers
- Chinese Academy of SciencesCN5 papers
- Hewlett Packard Enterprise (United States)US5 papers
- Norwegian University of Science and TechnologyNO5 papers
- Singapore Management UniversitySG5 papers
- University of Electronic Science and Technology of ChinaCN5 papers
- Agency for Science, Technology and ResearchSG4 papers
- Beihang UniversityCN4 papers
- Hong Kong Polytechnic UniversityHK4 papers
- Imperial College LondonGB4 papers
6 papers · 1 filter
Toward the Cognitive--Physical Limits of Embodied Intelligence through a World-Model-Centric Autonomous Racing Agent
Zitong Shan, Baichuan Lou, Yanxin Zhou +8
Embodied artificial intelligence aims to develop agents that perceive, reason, and act through continuous interaction with the physical world. However, most embodied systems are st…
A Wearable Stiffness-Rendering Haptic Device with a Honeycomb Jamming Mechanism for Bilateral Teleoperation
Thomas M. Kwok, Bohan Zhang, Wai Tuck Chow
This paper addresses the challenge of providing kinesthetic feedback in bilateral teleoperation by designing a wearable, lightweight (20 g), and compact haptic device, the HJ-Hapti…
SkillPlug: Unsupervised Skill Mining for Few-Shot Adaptation in Robotic Manipulation
Zi-han Ding, Ziwei Wang
Learning transferable visuomotor imitation policies that generalize across diverse manipulation tasks and adapt rapidly to new tasks from only a handful of demonstrations remains c…
Delta6: A Low-Cost, 6-DOF Force-Sensing Flexible End-Effector
Yue Feng, Weicheng Huang, Chen Qiu +2
This paper presents Delta6, a low-cost, six-degree-of-freedom (6-DOF) force/torque end-effector that combines antagonistic springs with magnetic encoders to deliver accurate wrench…
UniLGL: Learning Uniform Place Recognition for FOV-limited/Panoramic LiDAR Global Localization
Hongming Shen, Xun Chen, Yulin Hui +5
Existing LGL methods typically consider only partial information (e.g., geometric features) from LiDAR observations or are designed for homogeneous LiDAR sensors, overlooking the u…
An Intention-driven Lane Change Framework Considering Heterogeneous Dynamic Cooperation in Mixed-traffic Environment
Xiaoyun Qiu, Haichao Liu, Yue Pan +2
In mixed-traffic environments, autonomous vehicles (AVs) must interact with heterogeneous human-driven vehicles (HVs) whose intentions and driving styles vary across individuals an…