24 accepted papers
Lizards are capable of climbing stably on various terrains. Their tails are key to this ability. The lizard uses its flexible tail with graded stiffness as a fifth limb and climbing aid. The tail also enables soft landings, preventing injury from falls. Inspired by this, tails have been incorporated
Soft-bodied crawling animals exhibit efficient and adaptive behaviors resulting from the synergy between morphological computation (e.g., a flexible soft body and anisotropic skin) and neural computation (e.g., neural control with plasticity and short-term memory (STM)). However, applying these prin
Artificial neural networks can be used to solve a variety of robotic tasks. However, they risk failing catastrophically when faced with out-of-distribution (OOD) situations. Several approaches have employed a type of synaptic plasticity known as Hebbian learning that can dynamically adjust weights b
Animals exhibit remarkable adaptability in sensing their environments, employing strategies that optimize information gathering. For instance, silk moths adjust their wingflapping frequency to detect pheromones, while dogs modify their sniffing behavior by altering sniff height and frequency based o
Existing robot locomotion learning techniques rely heavily on the offline selection of proper reward weighting gains and cannot guarantee constraint satisfaction (i.e., constraint violation) during training. Thus, this work aims to address both issues by proposing Reward-Oriented Gains via Embodied…
The concept of morphological computation (MC) is applied in the robotics field to improve the design and reduce the complexity of control systems. The MC uses mechanical intelligence, where stiffness properties play an important role as constraints to enhance system flexibility and to store elastic
Achieving reliable navigation for autonomous drones in complex environments remains a significant challenge, particularly in low-light conditions. To address this, we propose an integrated multimodal obstacle detection and adaptive neural control system with online learning to enable drones to navig
Legged animals still outperform many terrestrial robots due to the complex interplay of various component subsystems. Centralization is a potential integrated design axis to help improve the performance of legged robots in variable terrain environments. Centralization arises from the coupling of mul
In the oil and gas industry, scale accumulation on radiant coils within furnaces significantly reduces heat-transfer efficiency, leading to increased energy consumption. This paper introduces the REFINE-bot, a robotic system developed to improve the descaling process and operational efficiency in fi
Partner diversity is known to be crucial for training a robust generalist cooperative agent. In this paper, we show that partner specialization, in addition to diversity, is crucial for the robustness of a downstream generalist agent. We propose a principled method for quantifying both the diversity…
While lower-limb exoskeletons have been increasingly used for gait assistance and rehabilitation, most of them continue to function as assistive devices in the exoskeleton-user relationship as a leader and follower. This limits the user’s ability to interactively contribute to gait control. Therefor…
In this work, we address the challenges of robust precision landing maneuvers for a quadrotor on both stationary and moving ground targets in the presence of disturbances that can cause the quadrotor to deviate from its desired trajectory, leading to maneuver failure. To overcome this, we propose a…
Conventional approaches in robotics for perceiving the environment and signaling the robot’s state or intention for human-robot interaction involve the use of separate sensing and signaling systems. This can sometimes result in high costs and complex system installations. In this study, we propose a…
Lateral undulation patterns of a flexible spine, including standing waves, traveling waves, and their transitions, enable agile and versatile locomotion in sprawling animals. Inspired by this, we proposed body-wave transition strategies for energy-efficient inclined-surface climbing of a gecko-inspi
While different control approaches have been developed for smooth and safe navigation, they are limited by the needs for model-based assumptions, true training target/reward function, and/or large sample data. To overcome these limitations, this study proposes a model-free neural control architectur…
Training a robust cooperative agent requires diverse partner agents. However, obtaining those agents is difficult. Previous works aim to learn diverse behaviors by changing the state-action distribution of agents. But, without information about the task's goal, the diversified agents are not guided…
Grasping multiple object types (versatile object grasping) with a single gripper is always a challenging task in robotic manipulation. Different types of grippers, including rigid and soft, have been developed to try to achieve the task. However, each gripper type is still restricted to specific obj
Typically, control strategies for legged robots have been developed to adapt their leg movements to deal with complex terrain. When the legs are extended in search of ground contact to support the robot body, this can result in the center of gravity (CoG) being raised higher from the ground and can
Adaptive systems enable legged robots to cope with a wide range of environmental settings and unforeseen events. Existing reactive methods adapt either the walking frequency or the amplitude to only simple perturbations. This letter proposes an adaptive mechanism for central pattern generator (CPG)-
Interactive (mechanical) impedance and finger fatigues are important topics, which have not been well investigated. To tackle this problem, we developed a soft lightweight (0.25 kg) finger exoskeleton (TIE-EXO) for quantifying interactive impedance and finger fatigue. A resist-as-needed (RAN) contro…
Sprawling posture animals with their bendable spine, such as salamanders, and geckos, can perform agile and versatile locomotion including walking, swimming, and climbing. Therefore, several roboticists have used them as templates for robot designs to investigate and generate efficient locomotion. T
In this letter, we present an online learning mechanism called the dual integral learner for fast frequency adaptation in neural central pattern generator (CPG) based locomotion control of a hexapod robot. The mechanism works by modulating the CPG frequency through synaptic plasticity of the neural
In order to use walking robots for exploration in a real complex environment, an adaptive control system is required to allow them to successfully and efficiently traverse the terrains. To achieve this, we propose here our adaptive locomotion control technique of a walking robot. It is based on a mo…