Robotics aims to develop manipulation skills approaching human performance. However, skill complexity is often over- or underestimated based on individual experience, and the real-world performance gap is difficult or expensive to measure through in-person competitions. To bridge this gap, we propose a compact, internet-connected, electronic task board to measure manipulation … [Read more...] about Digital Robot Judge: Building a Task-Centric Performance Database of Real-World Manipulation With Electronic Task Boards
Robot sensing systems
Deep Predictive Model Learning With Parametric Bias: Handling Modeling Difficulties and Temporal Model Changes
When a robot executes a task, it is necessary to model the relationship among its body, target objects, tools, and environment, and to control its body to realize the target state. However, it is difficult to model them using classical methods if the relationship is complex. In addition, when the relationship changes with time, it is necessary to deal with the temporal changes … [Read more...] about Deep Predictive Model Learning With Parametric Bias: Handling Modeling Difficulties and Temporal Model Changes
Variable Stiffness, Sensing, and Healing in FESTO’s FinRay Gripper: An Industry-Driven Design
Soft grippers' rising popularity in industries is due to their impressive adaptability. Yet, this adaptability requires flexibility which often sacrifices grip firmness and complicates sensor integration. This paper introduces two additional innovations, variable stiffness and pneumatic sensing, into a FinRay adaptive gripper. The approach and design for incorporating these … [Read more...] about Variable Stiffness, Sensing, and Healing in FESTO’s FinRay Gripper: An Industry-Driven Design
Distributed Optimization Methods for Multi-Robot Systems: Part 2—A Survey
Although the field of distributed optimization is well developed, relevant literature focused on the application of distributed optimization to multi-robot problems is limited. This survey constitutes the second part of a two-part series on distributed optimization applied to multi-robot problems. In this article, we survey three main classes of distributed optimization … [Read more...] about Distributed Optimization Methods for Multi-Robot Systems: Part 2—A Survey
Radar-Based Fall Detection: A Survey [Survey]
Fall detection, particularly critical for high-risk demographics like the elderly, is a key public health concern, where timely detection can greatly minimize harm. With the advancements in radio frequency (RF) technology, radar has emerged as a powerful tool for human fall detection. Traditional machine learning (ML) algorithms, such as support vector machines (SVM) and k … [Read more...] about Radar-Based Fall Detection: A Survey [Survey]