9 accepted papers
Humanoid robots encounter considerable difficulties in autonomously recovering from falls, especially within dynamic and unstructured environments. Conventional control methodologies are often inadequate in addressing the complexities associated with high-dimensional dynamics and the contact-rich na
Mobile manipulators enable a wide range of operations with mobility and advanced manipulation capabilities. Despite their potential, existing approaches typically treat the mobile base and the manipulator separately, thereby limiting the optimality of the system for composite whole-body behaviors. I
The robustness of legged locomotion is crucial for quadrupedal robots in challenging terrains. Recently, Reinforcement Learning (RL) has shown promising results in legged locomotion and various methods try to integrate privileged distillation, scene modeling, and external sensors to improve the gene…
Despite the impressive performance of Reinforcement Learning (RL), the black-box neural network backbone hinders users from trusting and deploying trained agents in real-world applications where safety is crucial. In order to make agents more trustworthy and controllable, for a given RL-trained poli…
The hierarchical quadratic programming (HQP) is commonly applied to consider strict hierarchies of multi-tasks and robot's physical inequality constraints during whole-body compliance. However, for the one-step HQP, the solution can oscillate when it is close to the boundary of constraints. It is be…
Whole-body control (WBC) with task priority transition is an important technology for robots to switch multiple behaviors, change different objectives, and adapt to various environments. Many methods have solved the problem of control continuity in the priority transition process. However, they eith…
For achieving kinematically suitable configurations and highly dynamic task execution, an efficient way is to consider robot performance indices in the whole-body control (WBC) of robots. However, current WBC methods have not considered the intrinsic features of parallel robots, especially motion/fo…
This work considers the control of underactuated bipedal walking, and a novel capturability-based control framework is presented. Compared with traditional approaches, the presented control method does not rely on the use of the Poincaré map, which may take significant computational cost. Firstly, a…
The planning of whole-body motion and step time for bipedal locomotion is constructed as a model predictive control (MPC) problem, in which a sequence of optimization problems needs to be solved online. While directly solving these problems is extremely time-consuming, we propose a predictive gait s