Learning Full-Body Motions from Monocular Vision in Real-Time: Dynamic Imitation in a Humanoid Robot
نویسندگان
چکیده
Learning Full-Body Motions from Monocular Vision in Real-Time: Dynamic Imitation in a Humanoid Robot
منابع مشابه
Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids
We seek intuitive, e cient ways to create and direct human-like behaviors for humanoid robots. Here we present a method to enable humanoid robots to acquire movements by imitation. The robot uses 3D vision to perceive the movements of a human teacher, and then estimates the teacher's body postures using a fast full-body inverse kinematics method that incorporates a kinematic model of the teache...
متن کاملImitation Learning of Robot Movement Using Evolutionary Algorithm
This paper presents a new framework to generate human-like movement of a humanoid robot in real time using the movement primitive database of a human. The framework consists of two processes: (1) the offline motion imitation learning based on Evolutionary Algorithm and (2) the movement generation of a humanoid robot using the database updated by the motion imitation learning. For the offline pr...
متن کاملLearning Actions through Imitation and Exploration: Towards Humanoid Robots That Learn from Humans
A prerequisite for achieving brain-like intelligence is the ability to rapidly learn new behaviors and actions. A fundamental mechanism for rapid learning in humans is imitation: children routinely learn new skills (e.g., opening a door or tying a shoe lace) by imitating their parents; adults continue to learn by imitating skilled instructors (e.g., in tennis). In this chapter, we propose a pro...
متن کاملReal-time full body motion imitation on the COMAN humanoid robot
On-line full body imitation with a humanoid robot standing on its own two feet requires simultaneously maintaining the balance and imitating the motion of the demonstrator. In this paper we present a method that allows real-time motion imitation while maintaining stability, based on prioritized task control. We also describe a method of modified prioritized kinematic control that constrains the...
متن کاملDynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference
We tackle the problem of learning imitative wholebody motions in a humanoid robot using probabilistic inference in Bayesian networks. Our inference-based approach affords a straightforward method to exploit rich yet uncertain prior information obtained from human motion capture data. Dynamic imitation implies that the robot must interact with its environment and account for forces such as gravi...
متن کامل