13 accepted papers
Recent advances in quadrupedal locomotion have focused on improving stability and performance across diverse environments. However, existing methods often lack adequate safety analysis and struggle to adapt to varying payloads and complex terrains, typically requiring extensive tuning. To overcome t…
Intra-class terrain differences such as water content directly influence a vehicle’s ability to traverse terrain, yet RGB vision systems may fail to distinguish these properties. We argue that expanding the evaluation of a terrain’s spectral content beyond red-green-blue channels to the near infrare…
Tactile sensing allows robots to gather detailed geometric information about objects through physical interaction, complementing vision-based approaches. However, efficiently acquiring useful tactile data remains challenging due to the time-consuming nature of physical contact and the need to strate…
We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than prev…
Recent advances in quadrupedal locomotion have focused on improving stability and performance across diverse environments. However, existing methods often lack adequate safety analysis and struggle to adapt to varying payloads and complex terrains, typically requiring extensive tuning. To overcome t
Traditional approaches to motion modeling for skid-steer robots struggle to capture nonlinear tire-terrain dynamics, especially during high-speed maneuvers. In this paper, we tackle such nonlinearities by enhancing a dynamic unicycle model with Gaussian Process (GP) regression outputs. This enables
We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than prev
Object 6D pose estimation is a critical challenge in robotics, particularly for manipulation tasks. While prior research combining visual and tactile (visuotactile) information has shown promise, these approaches often struggle with generalization due to the limited availability of visuotactile data
Learning for robot navigation presents a critical and challenging task. The scarcity and costliness of real-world datasets necessitate efficient learning approaches. In this letter, we exploit Euclidean symmetry in planning for 2D navigation, which originates from Euclidean transformations between r
Performance measures are essential to characterize a robot's ability to carry out manipulation tasks. Generally, these measures examine the system's kinematic transformations from configuration to task space, but the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.o
Humans are superior to robots in performing complex assembly tasks primarily due to their dexterity and sensorimotor abilities. When humans and robots collaborate to complete an assembly task, it is critical to provide the robot with sufficiently precise manipulation capabilities and formulate a sha
State-of-the-art human-in-the-loop robot grasping is hugely suffered by Electromyography (EMG) inference robustness issues. As a workaround, researchers have been looking into integrating EMG with other signals, often in an ad hoc manner. In this paper, we are presenting a method for end-to-end trai…
Predicting human trajectories is an important component of autonomous moving platforms, such as social robots and self-driving cars. Human trajectories are affected by both the physical features of the environment and social interactions with other humans. Despite recent surge of studies on human pa…