Time-optimal trajectory planning method for six-legged robots under actuator constraints

2019 ◽  
Vol 233 (14) ◽  
pp. 4990-5002
Author(s):  
Zhijun Chen ◽  
Feng Gao
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimization Problem ◽  
The Body ◽  
Planning Method ◽  
Legged Robots ◽  
Legged Robot ◽  
Time Optimal ◽  
Actuator Constraints ◽  
Optimal Trajectory Planning

Current studies on time-optimal trajectory planning centers on cases with fixed base and only one end-effector. However, the free-floating body and the multiple legs of the legged robot make the current methods inapplicable. This paper proposes a time-optimal trajectory planning method for six-legged robots. The model of the optimization problem for six-legged robots is built by considering the base and the end-effectors separately. Both the actuator constraints and the gait cycle constraints are taken into account. A novel two-step optimization method is proposed to solve the optimization problem. The first step solves the time-optimal trajectory of the body and the second step solves the time-optimal trajectory of the swinging legs. Finally, the method is applied to a six-parallel-legged robot and validated by experiments on the prototype. The results show that the velocity of the optimized gait is improved by 17.8% in contrast to the non-optimized one.

A Novel Algorithm for Time Optimal Trajectory Planning

2014 ◽  
Author(s):  
Mingxing Yuan ◽  
Bin Yao ◽  
Dedong Gao ◽  
Xiaocong Zhu ◽  
Qingfeng Wang
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
Problem Of Time ◽  
High Productivity ◽  
Hard Constraints ◽  
Time Optimal ◽  
Rate Optimization ◽  
Feed Rate Optimization ◽  
Optimal Trajectory Planning

Time optimal trajectory planning under various hard constraints plays a significant role in simultaneously meeting the requirements on high productivity and high accuracy in the fields of both machining tools and robotics. In this paper, the problem of time optimal trajectory planning is first formulated. A novel back and forward check algorithm is subsequently proposed to solve the minimum time feed-rate optimization problem. The basic idea of the algorithm is to search the feasible solution in the specified interval using the back or forward operations. Four lemmas are presented to illustrate the calculating procedure of optimal solution and the feasibility of the proposed algorithm. Both the elliptic curve and eight profile are used as case studies to verify the effectiveness of the proposed algorithm.

An optimal trajectory planning method for path tracking of industrial robots

Robotica ◽  
2018 ◽  
Vol 37 (3) ◽  
pp. 502-520 ◽  
Author(s):  
Xianxi Luo ◽  
Shuhui Li ◽  
Shubo Liu ◽  
Guoquan Liu
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Path ◽  
Path Tracking ◽  
Industrial Robots ◽  
Planning Method ◽  
Coordinate Frame ◽  
Optimization Approach ◽  
Cartesian Coordinate ◽  
Optimal Trajectory Planning

SUMMARYThis paper presents an optimal trajectory planning method for industrial robots. The paper specially focuses on the applications of path tracking. The problem is to plan the trajectory with a specified geometric path, while allowing the position and orientation of the path to be arbitrarily selected within the specific ranges. The special contributions of the paper include (1) an optimal path tracking formulation focusing on the least time and energy consumption without violating the kinematic constraints, (2) a special mechanism to discretize a prescribed path integration for segment interpolation to fulfill the optimization requirements of a task with its constraints, (3) a novel genetic algorithm (GA) optimization approach that transforms a target path to be tracked as a curve with optimal translation and orientation with respect to the world Cartesian coordinate frame, (4) an integration of the interval analysis, piecewise planning and GA algorithm to overcome the challenges for solving the special trajectory planning and path tracking optimization problem. Simulation study shows that it is an insufficient condition to define a trajectory just based on the consideration that each point on the trajectory should be reachable. Simulation results also demonstrate that the optimal trajectory for a path tracking problem can be obtained effectively and efficiently using the proposed method. The proposed method has the properties of broad adaptability, high feasibility and capability to achieve global optimization.

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