6 accepted papers
Exoskeleton robots are an effective method for enhancing human walking ability. This paper introduces a quasi-passive variable stiffness ankle exoskeleton, which absorbs negative work produced during ankle dorsiflexion in the stance phase of the gait cycle and releases energy to assist plantar flexi
In industrial applications, precision and load capacity are critical performance metrics for robotic arms. These requirements are typically addressed using high-gear-ratio designs. However, robotic arms are increasingly tasked with high-dynamic operations, such as smashes in sports and object throwi
In light of the widespread utilization of deep neural networks in various natural language tasks, adversarial attacks targeting these models have emerged as a significant concern. Through the introduction of subtle perturbations via word substitution, word-level adversarial attacks have demonstrated…
Deep neural networks exhibit vulnerability to word-level adversarial attacks in natural language processing. Most of these attack methods adopt synonymous substitutions to perturb original samples for crafting adversarial examples while attempting to maintain semantic consistency with the originals.…
Tactile sensation is one of the most important sensing methods of humans, which helps humans complete complex decisions and actions by itself or in cooperation with other sensations. Similarly, tactile sensors are also crucial for robots to interact with the environment and fulfill dexterous object
Gaits and transitions are key components in legged locomotion. For legged robots, describing and reproducing gaits as well as transitions remain longstanding challenges. Reinforcement learning has become a powerful tool to formulate controllers for legged robots. Learning multiple gaits and transiti