Related papers: Soft Robotic Dynamic In-Hand Pen Spinning
This paper presents the application of a learning control approach for the realization of a fast and reliable pick-and-place application with a spherical soft robotic arm. The arm is characterized by a lightweight design and exhibits…
Soft robots are intrinsically capable of adapting to different environments by changing their shape in response to interaction forces with the environment. However, sensing and feedback are still required for higher level decisions and…
In-hand manipulation of pen-like objects is an important skill in our daily lives, as many tools such as hammers and screwdrivers are similarly shaped. However, current learning-based methods struggle with this task due to a lack of…
Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. Soft continuum manipulators do not currently consider dynamic parameters when operating in task space. This shortcoming makes…
Soft robots have the potential to revolutionize the use of robotic systems with their capability of establishing safe, robust, and adaptable interactions with their environment, but their precise control remains challenging. In contrast,…
We propose a system to deliver dynamic guidance in drawing, sketching and handwriting tasks via an electromagnet moving underneath a high refresh rate pressure sensitive tablet. The system allows the user to move the pen at their own pace…
Robotic manipulation has made significant advancements, with systems demonstrating high precision and repeatability. However, this remarkable precision often fails to translate into efficient manipulation of thin deformable objects. Current…
We want to enable fine manipulation with a multi-fingered robotic hand by using modern deep reinforcement learning methods. Key for fine manipulation is a spatially resolved tactile sensor. Here, we present a novel model of a tactile skin…
Soft robots are notoriously hard to control. This is partly due to the scarcity of models able to capture their complex continuum mechanics, resulting in a lack of control methodologies that take full advantage of body compliance. Currently…
Autonomous grasping remains challenging as unlike humans, robots do not possess a sophisticated sensing nor delicate interaction capability with the real environment. Among other efforts that tried to close the gap between them,…
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,…
Some of the threats in the dynamic environment include the unpredictability of the motion of objects and interferences to the robotic grasp. In such conditions the traditional supervised and reinforcement learning approaches are ill suited…
Soft robots offer more flexibility, compliance, and adaptability than traditional rigid robots. They are also typically lighter and cheaper to manufacture. However, their use in real-world applications is limited due to modeling challenges…
Safe yet stable grasping requires a robotic hand to apply sufficient force on the object to immobilize it while keeping it from getting damaged. Soft robotic hands have been proposed for safe grasping due to their passive compliance, but…
This paper presents a soft robot finger capable of adaptive-twist deformation to grasp objects by wrapping them. For a soft hand to grasp and pick-up one object from densely contained multiple objects, a soft finger requires the…
Robots can influence people to accomplish their tasks more efficiently: autonomous cars can inch forward at an intersection to pass through, and tabletop manipulators can go for an object on the table first. However, a robot's ability to…
In this paper, a reinforced soft robot prototype with a custom-designed actuator-space string encoder are created to investigate dynamic soft robotic trajectory tracking. The soft robot prototype embedded with the proposed adaptive…
We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes…
Many possible fields of application of robots in real world settings hinge on the ability of robots to grasp objects. As a result, robot grasping has been an active field of research for many years. With our publication we contribute to the…
To ensure that a robot is able to accomplish an extensive range of tasks, it is necessary to achieve a flexible combination of multiple behaviors. This is because the design of task motions suited to each situation would become increasingly…