9 accepted papers
Knowledge distillation (KD) aims to enhance the performance of lightweight student networks through the guidance of teacher models. However, the existing methods have deficiencies in two key aspects: First, these methods rely heavily on static representation alignment, failing to account for optimiz
In this work, we conducted research on deformable object manipulation by robots based on demonstration-enhanced reinforcement learning (RL). We present FADERL (FuzzyAugmented Demonstration-Embedded Reinforcement Learning),a novel framework for robotic manipulation of deformable objects that signific…
In cluttered environments, a human-following mobile robot must predict the motion intention of the followed human and take environmental obstacles into consideration. Consequently, it brings several challenges, such as the human’s detour direction prediction problem and the visibility maintenance pr
In human-robot systems, ensuring safety during force control in the presence of both internal and external disturbances is crucial. As a typical loosely coupled floating-base robot system, the supernumerary robotic leg (SRL) system is particularly susceptible to strong internal disturbances. To addr
Environment awareness is crucial for enhancing walking safety and stability of amputee wearing powered prosthesis when crossing uneven terrains such as stairs and obstacles. However, existing environmental perception systems for prosthesis only provide terrain types and corresponding parameters, whi…
Gait phase-based control is a trending research topic for walking-aid robots, especially robotic lower-limb prostheses. Gait phase estimation is a challenge for gait phase-based control. Previous researches used the integration or the differential of the human's thigh angle to estimate the gait phas
Researchers are currently making progress in unifying the entire gait cycle of powered prostheses by using a human-inspired phase variable, but constructing a robust phase variable to more accurately estimate the gait phase and desired joint trajectories of prostheses during varying walking speeds r
Firstly, in the letter [1], there is a missing citation in Section II, part B, the first sentence. It should be “In a manner similar to [2], [3], speed estimation was achieved by a double-pendulum model.” In our previous version [1], speed estimation was based on the principles in [3]. We also refer
Predicting the locomotion intent of humans is important for controlling assistive robots. Previous studies have investigated assistive walking on structured terrains, but only a few studies have considered rough terrains. Human intent on rough terrains is more difficult to predict because there is a