12 accepted papers
To achieve human-like skin tactile perception with super-resolution, the method of introducing a soft layer on sensing array has attracted increasing attention. Due to the limitations of sensing units principle, most existing tactile sensors can only sense normal force. However, multi-dimensional fo…
Achieving human-like dexterous robotic manipulation remains a central goal and a pivotal challenge in robotics. The development of Artificial Intelligence (AI) has allowed rapid progress in robotic manipulation. This survey summarizes the evolution of robotic manipulation from mechanical programming…
Mobile manipulators integrate the locomotion flexibility of quadruped robots with the operational capabilities of robotic manipulators. This integrated system is particularly effective for teleoperating explosive ordnance disposal (EOD) tasks in hazardous environments, enabling the safe handling of
Vision and touch are the most commonly used senses in human manipulation. While leveraging human manipulation videos for robotic task pretraining has shown promise in prior works, it is limited to image and language modalities and deployment to simple parallel grippers. In this paper, aiming to addr…
Recently, pre-trained vision models have gained significant attention in motor control, showcasing impressive performance across diverse robotic learning tasks. While previous works predominantly concentrate on the significance of the pre-training phase, the equally important task of extracting more…
Recent works on the pretraining for robot manipulation have demonstrated that representations learning from large human manipulation data can generalize well to new manipulation tasks and environments. However, these approaches mainly focus on human vision or natural language, neglecting tactile fee…
Hand motion tracking is essential in many fields, e.g., immersive virtual reality, teleoperation of robotic hand, and hand rehabilitation of stroke patient, as human hand plays a crucial role in our daily life. The highly under-actuated hand exoskeleton, which can track the 6-DoF motions of each fin…
Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep re-inforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action spa…
The workspace limit to smoothly map unreachable motions sensed in the leader side$^1$ to the reachable workspace of the follower robot is fundamental for teleoperation systems. Although numerous workspace determination methods have been studied, the workspace limit approach still remains challenging
Orientability is an important performance index to evaluate the dexterity of haptic master devices. Currently, most of the existing haptic master devices have limited workspace and limited dexterity. In this paper, we present the RemoT-ARM, a 6 Degree-of-Freedom (DOF) haptic master device that can p…
Teleoperation systems require a human-centered approach in which the kinematic mapping is intuitive and straightforward for the operators. However, a mismatch in the degrees-of-freedom (DoFs) between master and slave could result in an asymmetrical teleoperation system. That is an obstacle for intui
Orientation control is an important topic with many applications including robotic manipulation, spacecraft control, etc. The orientation control is particularly challenging when the system model is unknown due to the fact that the rotation group is a nonlinear manifold. In this letter, we propose a