Dynamically-Stable Motion Planning for Humanoid Robots
Autonomous Robots
An inverse kinematics architecture enforcing an arbitrary number of strict priority levels
The Visual Computer: International Journal of Computer Graphics - Special section on implicit surfaces
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Steering a humanoid robot by its head
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Interactive control of humanoid navigation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Task Sequencing for High-Level Sensor-Based Control
IEEE Transactions on Robotics
Planning 3-D Collision-Free Dynamic Robotic Motion Through Iterative Reshaping
IEEE Transactions on Robotics
Task-driven posture optimization for virtual characters
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Task-driven posture optimization for virtual characters
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Robotics and artificial intelligence: A perspective on deliberation functions
AI Communications - ECAI 2012 Turing and Anniversary Track
| Hi-index | 0.00 |
We present a novel approach to plan foot placements for a humanoid robot according to kinematic tasks. In this approach, the foot placements are determined by the continuous deformation of a robot motion including a locomotion phase according to the desired tasks. We propose to represent the motion by a virtual kinematic tree composed of a kinematic model of the robot and articulated foot placements. This representation allows us to formulate the motion deformation problem as a classical inverse kinematics problem on a kinematic tree. We first provide details of the basic scheme where the number of footsteps is given in advance and illustrate it with scenarios on the robot HRP-2. Then we propose a general criterion and an algorithm to adapt the number of footsteps progressively to the kinematic goal. The limits and possible extensions of this approach are discussed last.