### Abstract

Manipulator joint trajectories are sought to optimize a specified cost function under preplanned path constraints, taking into consideration the physical constraints on the kinematics and dynamics of the system. Using a time-scale factor kappa (t) and a set of joint trajectories representing a geometric path, all joint trajectories tracing the path are described as a function of kappa (t) and its time derivative. Then the desirable kappa (t) is obtained by two methods: a global optimization method using dynamic programming (DP), and an iteratively improving (II) method, which is a feasible method and utilizes the local controllability of B-splines. These methods are applied to joint trajectory planning of a preplanned collision-free path of a manipulator. The numerical results show that the II method is more effective than the DP method with respect to computation time and memory requirements if a strictly optimal solution is not required.

Original language | English |
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Pages (from-to) | 1029-1034 |

Number of pages | 6 |

Journal | Proceedings of the IEEE Conference on Decision and Control |

Publication status | Published - Dec 1 1987 |

Externally published | Yes |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Control and Systems Engineering
- Modelling and Simulation
- Control and Optimization

### Cite this

*Proceedings of the IEEE Conference on Decision and Control*, 1029-1034.

**OPTIMAL AND NEAR-OPTIMAL MANIPULATOR JOINT TRAJECTORIES WITH A PREPLANNED PATH.** / Ozaki, H.; Yamamoto, M.; Mohri, A.

Research output: Contribution to journal › Conference article

*Proceedings of the IEEE Conference on Decision and Control*, pp. 1029-1034.

}

TY - JOUR

T1 - OPTIMAL AND NEAR-OPTIMAL MANIPULATOR JOINT TRAJECTORIES WITH A PREPLANNED PATH.

AU - Ozaki, H.

AU - Yamamoto, M.

AU - Mohri, A.

PY - 1987/12/1

Y1 - 1987/12/1

N2 - Manipulator joint trajectories are sought to optimize a specified cost function under preplanned path constraints, taking into consideration the physical constraints on the kinematics and dynamics of the system. Using a time-scale factor kappa (t) and a set of joint trajectories representing a geometric path, all joint trajectories tracing the path are described as a function of kappa (t) and its time derivative. Then the desirable kappa (t) is obtained by two methods: a global optimization method using dynamic programming (DP), and an iteratively improving (II) method, which is a feasible method and utilizes the local controllability of B-splines. These methods are applied to joint trajectory planning of a preplanned collision-free path of a manipulator. The numerical results show that the II method is more effective than the DP method with respect to computation time and memory requirements if a strictly optimal solution is not required.

AB - Manipulator joint trajectories are sought to optimize a specified cost function under preplanned path constraints, taking into consideration the physical constraints on the kinematics and dynamics of the system. Using a time-scale factor kappa (t) and a set of joint trajectories representing a geometric path, all joint trajectories tracing the path are described as a function of kappa (t) and its time derivative. Then the desirable kappa (t) is obtained by two methods: a global optimization method using dynamic programming (DP), and an iteratively improving (II) method, which is a feasible method and utilizes the local controllability of B-splines. These methods are applied to joint trajectory planning of a preplanned collision-free path of a manipulator. The numerical results show that the II method is more effective than the DP method with respect to computation time and memory requirements if a strictly optimal solution is not required.

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M3 - Conference article

AN - SCOPUS:0023569921

SP - 1029

EP - 1034

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

SN - 0191-2216

ER -