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Proceedings ArticleDOI

Optimal Task Planning of Humanoid in Cluttered Environment

About: The article was published on 2016-12-05. It has received 2 citations till now. The article focuses on the topics: Motion planning & Task (project management).
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TL;DR: An asymptotically optimal sampling based approach for generating motion plans is presented and a novel constraint solver extension to the bidirectional Fast Marching Trees algorithm in the form of a way-point generator is proposed such that it can be applied for whole-body motion planning of humanoids.

5 citations

Posted Content
TL;DR: A framework to learn coordinated tasks in cluttered environments based on DiGrad - A multi-task reinforcement learning algorithm for continuous action-spaces is proposed and it is observed that the humanoid is able to plan collision free trajectory in real-time.
Abstract: With the advent of artificial intelligence and machine learning, humanoid robots are made to learn a variety of skills which humans possess. One of fundamental skills which humans use in day-to-day activities is performing tasks with coordination between both the hands. In case of humanoids, learning such skills require optimal motion planning which includes avoiding collisions with the surroundings. In this paper, we propose a framework to learn coordinated tasks in cluttered environments based on DiGrad - A multi-task reinforcement learning algorithm for continuous action-spaces. Further, we propose an algorithm to smooth the joint space trajectories obtained by the proposed framework in order to reduce the noise instilled during training. The proposed framework was tested on a 27 degrees of freedom (DoF) humanoid with articulated torso for performing coordinated object-reaching task with both the hands in four different environments with varying levels of difficulty. It is observed that the humanoid is able to plan collision free trajectory in real-time. Simulation results also reveal the usefulness of the articulated torso for performing tasks which require coordination between both the arms.

Cites methods from "Optimal Task Planning of Humanoid i..."

  • ...[1]–[3] used the sampling based algorithms like PRM [4], RRT-connect [5], RRT*-connect [6] etc....

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