Humanoid robot

About: Humanoid robot is a research topic. Over the lifetime, 14387 publications have been published within this topic receiving 243674 citations. The topic is also known as: 🤖.

ZMP Support Areas for Multicontact Mobility Under Frictional Constraints

Abstract: We propose a method for checking and enforcing multicontact stability based on the zero-tilting moment point (ZMP). The key to our development is the generalization of ZMP support areas to take into account: 1) frictional constraints and 2) multiple noncoplanar contacts. We introduce and investigate two kinds of ZMP support areas. First, we characterize and provide a fast geometric construction for the support area generated by valid contact forces, with no other constraint on the robot motion. We call this set the full support area. Next, we consider the control of humanoid robots by using the linear pendulum mode (LPM). We observe that the constraints stemming from the LPM induce a shrinking of the support area, even for walking on horizontal floors. We propose an algorithm to compute the new area, which we call the pendular support area. We show that, in the LPM, having the ZMP in the pendular support area is a necessary and sufficient condition for contact stability. Based on these developments, we implement a whole-body controller and generate feasible multicontact motions where an HRP-4 humanoid locomotes in challenging multicontact scenarios.

Measuring empathy for human and robot hand pain using electroencephalography.

Abstract: This study provides the first physiological evidence of humans’ ability to empathize with robot pain and highlights the difference in empathy for humans and robots. We performed electroencephalography in 15 healthy adults who observed either human- or robot-hand pictures in painful or non-painful situations such as a finger cut by a knife. We found that the descending phase of the P3 component was larger for the painful stimuli than the non-painful stimuli, regardless of whether the hand belonged to a human or robot. In contrast, the ascending phase of the P3 component at the frontal-central electrodes was increased by painful human stimuli but not painful robot stimuli, though the interaction of ANOVA was not significant, but marginal. These results suggest that we empathize with humanoid robots in late top-down processing similarly to human others. However, the beginning of the top-down process of empathy is weaker for robots than for humans.

Humanoid Robot Locomotion and Manipulation Step Planning

Abstract: We aim at planning multi-contact sequences of stances and postures for humanoid robots. The output sequence defines the contact transitions that allow our robot to realize different kind of tasks, ranging from biped locomotion to dexterous manipulation. The central component of the planning framework is a best-first algorithm that performs a search of the contacts to be added or removed at each step, following an input collision-free guide path, and making calls to an optimization-based inverse kinematics solver under static equilibrium constraints. The planner can handle systems made of multiple robots and/or manipulated objects through a centralized multi-agent approach, opening the way for multi-robot collaborative locomotion and manipulation planning. Results are presented in virtual environments, with discussion on execution on the real robot HRP-2 in an example situation.

Collaborative Human-Humanoid Carrying Using Vision and Haptic Sensing

Abstract: We propose a framework for combining vision and haptic information in human-robot joint actions. It consists of a hybrid controller that uses both visual servoing and impedance controllers. This can be applied to tasks that cannot be done with vision or haptic information alone. In this framework, the state of the task can be obtained from visual information while haptic information is crucial for safe physical interaction with the human partner. The approach is validated on the task of jointly carrying a flat surface (e.g. a table) and then preventing an object (e.g. a ball) on top from falling off. The results show that this task can be successfully achieved. Furthermore, the framework presented allows for a more collaborative setup, by imparting task knowledge to the robot as opposed to a passive follower.

High frequency walking pattern generation based on preview control of ZMP

Abstract: This paper addresses a dynamically stable humanoid walking pattern generation system that can update the pattern at a short cycle such as 40 [ms]. Frequent update of the pattern enables a robot to reflect change of moving direction and upper body posture with short delay after the change of the command input. It also enables a robot to change the walking pattern according to the change of measurable applied force. Moreover short cycle generation is useful in constructing a system that reflects motion status modified by sensor feedback to the motion generation layer in order to maintain consistency of dynamics. Preview control theory is adopted to decide horizontal torso trajectory that realizes desired ZMP trajectory. The proposed system is implemented on a full-size humanoid HRP-2. Walking pattern is updated at every 40 [ms] with reflecting the current modified torso position in the system. Walking control is successfully carried out by the implemented system. Then an experiment of generating and executing walking pattern while variable force is applied to the hand is shown. The system generates walking pattern reflecting the force sensor information at the wrist while walking