The design, construction, and use of robots, as well as the use of computer systems for their control, sensory feedback, and information processing.
The paper introduces a design for Acoustic Soft Tactile (AST) Skin aimed at improving the precision of 2-D tactile feature estimation. The design utilizes acoustic energy through dedicated channels beneath…
Continue readingThe study presents the Open-World Mobile Manipulation System. This system enables robots to interact with articulated objects such as doors, cabinets, and refrigerators in unstructured environments like homes. The robot…
Continue readingThe article presents a new framework for Interactive Machine Learning (IML), aiming to incorporate human expertise into machine learning algorithms. The framework is grounded in Bayesian Optimization (BO), thus called…
Continue readingThis paper presents a new contact and wearable sensing system for estimating the posture and joint angles of the human body using foot pressure distribution information from a sensor on…
Continue readingThe paper discusses the design, development, and deployment of context-adaptive AI systems to improve end-user adoption. It emphasizes the importance of user-centered approaches in understanding user experiences with AI systems…
Continue readingThe paper investigates the challenge of recognizing distinct arm movements of robots in noisy environments using machine learning techniques. A vision system tracks the robot’s movements, and a deep learning…
Continue readingThe paper presents WindSeer, a neural network trained with synthetic data from computational fluid dynamics simulations. It predicts low-altitude wind in real-time on limited-compute devices using sparse measurement data. The…
Continue readingThe article discusses the use of machine learning techniques for robot dynamics learning and control. The authors propose a Hamiltonian formation of a neural ordinary differential equation (ODE) network to…
Continue readingThis paper presents a method to improve imitation learning in robots by focusing on data with a relatively low correlation to the desired output. The proposed approach inputs such data…
Continue readingThis paper addresses the challenge of controlling a drone in unknown dynamic environments using a new model predictive control (MPC) approach called hyMPC. The hyMPC leverages high-level decision variables to…
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