Related papers: TacGNN:Learning Tactile-based In-hand Manipulation…
The strength of the human hand lies in its ability to manipulate small objects precisely and robustly. In contrast, simple robotic grippers have low dexterity and fail to handle small objects effectively. This is why many automation tasks…
Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both effectiveness--reliable operation despite uncertain object structures--and efficiency--swift…
Tactile sensing is of great importance during human hand usage such as object exploration, grasping and manipulation. Different types of tactile sensors have been designed during the past decades, which are mainly focused on either the…
Touch sensing can help robots understand their sur- rounding environment, and in particular the objects they interact with. To this end, roboticists have, in the last few decades, developed several tactile sensing solutions, extensively…
Tactile sensing is an essential perception for robots to complete dexterous tasks. As a promising tactile sensing technique, vision-based tactile sensors have been developed to improve robot performance in manipulation and grasping. Here we…
The ability to perceive object slip via tactile feedback enables humans to accomplish complex manipulation tasks including maintaining a stable grasp. Despite the utility of tactile information for many applications, tactile sensors have…
Tactile perception is crucial for embodied intelligent robots to recognize objects. Vision-based tactile sensors extract object physical attributes multidimensionally using high spatial resolution; however, this process generates abundant…
Several robot manipulation tasks are extremely sensitive to variations of the physical properties of the manipulated objects. One such task is manipulating objects by using gravity or arm accelerations, increasing the importance of mass,…
Though robotic dexterous manipulation has progressed substantially recently, challenges like in-hand occlusion still necessitate fine-grained tactile perception, leading to the integration of more tactile sensors into robotic hands.…
Tactile sensing is critical to fine-grained, contact-rich manipulation tasks, such as insertion and assembly. Prior research has shown the possibility of learning tactile-guided policy from teleoperated demonstration data. However, to…
Observational learning is a promising approach to enable people without expertise in programming to transfer skills to robots in a user-friendly manner, since it mirrors how humans learn new behaviors by observing others. Many existing…
Many robotic hands currently rely on extremely dexterous robotic fingers and a thumb joint to envelop themselves around an object. Few hands focus on the palm even though human hands greatly benefit from their central fold and soft surface.…
Advanced dexterous manipulation involving multiple simultaneous contacts across different surfaces, like pinching coins from ground or manipulating intertwined objects, remains challenging for robotic systems. Such tasks exceed the…
Telemanipulation of deformable objects requires high precision and dexterity from the users, which can be increased by kinesthetic and tactile feedback. However, the object shape can change dynamically, causing ambiguous perception of its…
We investigate in-hand rolling manipulation using a multifingered robot hand, where each finger is compliant and equipped with a tactile fingertip providing contact location and wrench information. We derive the equations of motion for…
Robotic manipulation holds the potential to replace humans in the execution of tedious or dangerous tasks. However, control-based approaches are not suitable due to the difficulty of formally describing open-world manipulation in reality,…
Bimanual robotic manipulation is an emerging and critical topic in the robotics community. Previous works primarily rely on integrated control models that take the perceptions and states of both arms as inputs to directly predict their…
Robotic pushing is a fundamental manipulation task that requires tactile feedback to capture subtle contact forces and dynamics between the end-effector and the object. However, real tactile sensors often face hardware limitations such as…
Robotic manipulation requires both rich multimodal perception and effective learning frameworks to handle complex real-world tasks. See-through-skin (STS) sensors, which combine tactile and visual perception, offer promising sensing…
This paper introduces the TacFR-Gripper, a reconfigurable Fin Ray-based soft and compliant robotic gripper equipped with tactile skin, which can be used for dexterous in-hand manipulation tasks. This gripper can adaptively grasp objects of…