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Study on State Transition Method Applied to Motion Planning for a Humanoid Robot
| Content Provider | SAGE Publishing |
|---|---|
| Author | Wang, Xuyang Lu, Tiansheng Zhang, Peiyan |
| Copyright Year | 2008 |
| Abstract | This paper presents an approach of motion planning for a humanoid robot using a state transition method. In this method, motion planning is simplified by introducing a state-space to describe the whole motion series. And each state in the state-space corresponds to a contact state specified during the motion. The continuous motion is represented by a sequence of discrete states. The concept of the transition between two neighboring states, that is the state transition, can be realized by using some traditional path planning methods. Considering the dynamical stability of the robot, a state transition method based on search strategy is proposed. Different sets of trajectories are generated by using a variable 5th-order polynomial interpolation method. After quantifying the stabilities of these trajectories, the trajectories with the largest stability margin are selected as the final state transition trajectories. Rising motion process is exemplified to validate the method and the simulation results show the proposed method to be feasible and effective. |
| Related Links | https://journals.sagepub.com/doi/pdf/10.1177/172988140800500201?download=true |
| ISSN | 17298806 |
| Issue Number | 2 |
| Volume Number | 5 |
| Journal | International Journal of Advanced Robotic Systems (ARX) |
| e-ISSN | 17298814 |
| DOI | 10.1177/172988140800500201 |
| Language | English |
| Publisher | Sage Publications UK |
| Publisher Date | 2016-09-02 |
| Publisher Place | London |
| Access Restriction | Open |
| Rights Holder | © 2008 SAGE Publications Ltd |
| Rights License | Llicensed Under Creative Commons Licenses |
| Subject Keyword | state-space state transition motion planning humanoid robots |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Science Applications Software |