11 accepted papers
Reward function design remains a fundamental challenge in reinforcement learning of humanoid robots, where handcrafted rewards often fail to capture human-like behavior, limit generalization, and require costly manual tuning. Addressing this bottleneck is essential for enabling scalable, adaptive, i
The accuracy of path following is crucial for collision-free navigation of hyper-redundant robots, especially in narrow environments. However, the existing path following methods only consider the deviations of joints and the end effector, while ignoring the deviations of the robot body. In this let
During complex object manipulation, manipulator systems often face the configuration disconnectivity problem due to closed-chain constraints. Although regrasping can be adopted to guarantee connectivity, it introduces additional issues such as impact and efficiency. Therefore, regrasping numbers sho
Collision-free motion planning has a well-established research history, but the majority of studies have been centered around Euclidean space and conducted offline. The primary challenge in online motion planning lies in circumventing local minima, which become more pronounced in configuration space
Robot exploration aims at the reconstruction of unknown environments, and it is important to achieve it with shorter paths. Traditional methods focus on optimizing the visiting order of frontiers based on current observations, which may lead to local-minimal results. Recently, by predicting the stru
Collision-free motion planning has a well-established research history, yet the majority of studies have been centered around Cartesian space and assume the exact positions and shapes of the obstacles in the environment are known. In this letter, we introduce a perceptual local reactive motion contr
Topological maps are favorable for their small storage compared to geometric maps. However, they are limited in relocalization and path planning capabilities. To solve the problem, a feature-based hybrid topological map (FHT-Map) is proposed along with a real-time map construction algorithm based on
We present a forward kinematics method for object handling and transporting by a multi-robot team with a deformable sheet as a carrier. Due to the deformability of the sheet and the high dimension of the whole system, it is challenging to clearly describe all the possible positions of the object on
Rendezvous aims at gathering all robots at a specific location, which is an important collaborative behavior for multi-robot systems. However, in an unknown environment, it is challenging to achieve rendezvous. Previous researches mainly focus on special scenarios where communication is not allowed
Mutual localization serves as the foundation for collaborative perception in multi-robot systems. Effectively utilizing limited onboard sensors for mutual localization between marker-less robots is worthwhile. However, due to inadequate consideration of large scale variations of the robot and locali
Using a deformable sheet to handle objects is convenient and found in many practical applications. For object manipulation through a deformable sheet that is held by multiple mobile robots, it is a challenging task to model the object-sheet interactions. We present a computational model and algorith