This paper presents a robust and reliable humanrobot collaboration framework for bimanual manipulation. We propose an optimal motion adaptation method to retarget arbitrary human commands to feasible robot pose references while maintaining payload stability. The framework comprises three modules: (1) Task-Space Sequential Equilibrium and Inverse Kinematics Optimization for … [Read more...] about Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control: Retargeting Human Commands to Feasible Robot Control References
Robots
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
Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation
Dexterous in-hand manipulation in robotics, particularly with multi-fingered robotic hands, poses significant challenges due to the intricate avoidance of collisions among fingers and the object being manipulated. Collision-free paths for all fingers must be generated in real-time, as the rapid changes in hand and finger positions necessitate instantaneous recalculations to … [Read more...] about Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation
SofToss: Learning to Throw Objects With a Soft Robot
In this paper, we present, for the first time, a soft robot control system (SofToss) capable of throwing life-size objects toward target positions. SofToss is an open-loop controller based on deep reinforcement learning that generates, given the target position, an actuation pattern for the tossing task. To deal with the high non-linearity of the dynamics of soft robots, we … [Read more...] about SofToss: Learning to Throw Objects With a Soft Robot
Models of Human Behavior for Human–Robot Interaction and Automated Driving: How Accurate Do the Models of Human Behavior Need to Be?
There are many examples of cases where access to improved models of human behavior and cognition has allowed the creation of robots that can better interact with humans, and not least in road vehicle automation, this is a rapidly growing area of research. Human–robot interaction (HRI) therefore provides an important applied setting for human behavior modeling—but given the vast … [Read more...] about Models of Human Behavior for Human–Robot Interaction and Automated Driving: How Accurate Do the Models of Human Behavior Need to Be?
