14 accepted papers
Learning cooperative multi-agent policy from offline multi-task data that can generalize to unseen tasks with varying numbers of agents and targets is an attractive problem in many scenarios. Although aggregating general behavior patterns among multiple tasks as skills to improve policy transfer is…
Despite the growing integration of deep models into mobile terminals, the accuracy of these models declines significantly due to various deployment interferences. Test-time adaptation (TTA) has emerged to improve the performance of deep models by adapting them to unlabeled target data online. Yet, t…
Pneumatic actuated soft robots attract increasing interest of the researchers due to the availability and simplicity in actuation. The soft robots driven by soft pneumatic actuators (SPAs) of various active volumes demand pneumatic systems with various range of flow rate. However, the usually bulky
Soft robotic arms have gained significant attention owing to their flexibility and adaptability. Nonetheless, the instability due to their high-elasticity structure further leads to the difficulty of precise kinematic modeling and control. This letter introduces a novel solution employing foam-embed
Hydraulic-driven soft robots have received much less attention than their pneumatic counterparts. However, the incompressibility of liquid could bring a series of desirable attributes to soft robotic control, despite the apparent disadvantage of weight addition and compliance compromise resulting fr
Interactions with environmental objects can induce substantial alterations in both exteroceptive and proprioceptive signals. However, the deployment of exteroceptive sensors within underwater soft manipulators encounters numerous challenges and constraints, thereby imposing limitations on their perc
Sampling-based planning algorithms such as RRT have been proved to be efficient in solving path planning problems for robotic systems. Various improvements to the RRT algorithm have been presented to improve the performance of the extension and convergence of the random trees, such as Informed RRT*.…
Soft robots undergo complex deformations during actuation and interaction due to the flexibility and compliance of their soft materials. This characteristic presents challenges in proprioception, particularly in characterizing their spatial deformations. Soft optical waveguide sensors have emerged a
Soft robotic manipulators have inherent advantages in underwater applications, as they generate motion by deforming seamless muscles rather than having rotational joints or sliding cylinders, as well as having excellent passive adaptability. However, limited by insufficient structural stiffness, ach
Data-efficiency has always been an essential issue in pixel-based reinforcement learning (RL). As the agent not only learns decision-making but also meaningful representations from images. The line of reinforcement learning with data augmentation shows significant improvements in sample-efficiency.…
Proprioception and variable stiffness are two trending topics in soft robotics research. The former could endow soft robots with the ability to perceive the environment as well as their internal states without the need of dedicated sensors, while the latter could strengthen the otherwise excessive c…
The soft robotic manipulators attract extensive interest of researchers due to its conformity to the unstructured environment, safe-interaction with human and fragile objects. The movement of the soft manipulator often include elongation, contraction, 2-DOF rotations due to the parallelly arranged f
Proprioception is the ability to perceive environmental stimulations through internal sensory organs. Enabling proprioception is critical for robots to be aware of the environmental interactions and respond appropriately, particularly for high-payload grippers to ensure safety when handling delicate