Trajectory planning of mobile manipulators using dynamic programming approach

Robotica ◽  
2012 ◽  
Vol 31 (4) ◽  
pp. 643-656 ◽  
Author(s):  
M. H. Korayem ◽  
M. Irani ◽  
A. Charesaz ◽  
A. H. Korayem ◽  
A. Hashemi
Keyword(s):  
Dynamic Programming ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Vision System ◽  
Optimal Path ◽  
Optimization Method ◽  
Mobile Manipulator ◽  
Programming Approach ◽  
Planning Problem ◽  
Mobile Manipulators

SUMMARYThis paper presents a solution for optimal trajectory planning problem of robotic manipulators with complicated dynamic equations. The main goal is to find the optimal path with maximum dynamic load carrying capacity (DLCC). Proposed method can be implemented to problems of both motion along a specified path and point-to-point motion. Dynamic Programming (DP) approach is applied to solve optimization problem and find the positions and velocities that minimize a pre-defined performance index. Unlike previous attempts, proposed method increases the speed of convergence by using the sequential quadratic programming (SQP) formulation. This formulation is used for solving problems with nonlinear constraints. Also, this paper proposes a new algorithm to design optimal trajectory with maximum DLCC for both fixed and mobile base mechanical manipulators. Algorithms for DLCC calculations in previous works were based on indirect optimization method or linear programming approach. The proposed trajectory planning method is applied to a linear tracked Puma and the mobile manipulator named Scout. Application of this algorithm is confirmed and simulation results are compared with experimental results for Scout robot. In experimental test, results are obtained using a new stereo vision system to determine the position of the robot end-effector.

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.

Determination of the base position and working area for mobile manipulators

2016 ◽  
Vol 36 (1) ◽  
pp. 80-88 ◽  
Author(s):  
Shunan Ren ◽  
Xiangdong Yang ◽  
Jing Xu ◽  
Guolei Wang ◽  
Ying Xie ◽  
...  
Keyword(s):  
Operation Mode ◽  
Mobile Manipulator ◽  
Planning Problem ◽  
Mobile Manipulators ◽  
Line Planning ◽  
Content Type ◽  
Practical Applications ◽  
Base Position ◽  
Intersection Area ◽  
Intersection Line

Purpose – The purpose of this paper is to determine the base position and the largest working area for mobile manipulators. The base position determines the workspace of the mobile manipulator, particularly when the operation mode is intermittent (i.e. the mobile platform stops when the manipulator conducts the task). When the base of the manipulator is in the intersection area of the Base’s Workable Location Spaces (BWLSes), the end effector (EE) can reach all path points. In this study, the intersection line of BWLSes is calculated numerically, and the largest working area is determined using the BWLS concept. The performance of this method is validated with simulations on specific surface segments, such as plane, cylinder and conical surface segments. Design/methodology/approach – The BWLS is used to determine the largest working area and the base position in which the mobile manipulator can reach all path points with the objective of reducing off-line planning time. Findings – Without considering the orientation of the EE, the base position and the working area for the mobile manipulator are determined using the BWLS. Compared to other methods, the proposed algorithm is beneficial when the planning problem has six dimensions, ensuring the reachability and stability of the EE. Originality/value – The algorithm needs no manual configuration, and its performance is investigated for typical surfaces in practical applications.

ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH

2018 ◽  
Vol 34 (3) ◽  
pp. 381-405
Author(s):  
Ingeborg A. Bikker ◽  
Martijn R.K. Mes ◽  
Antoine Sauré ◽  
Richard J. Boucherie
Keyword(s):  
Dynamic Programming ◽  
Capacity Planning ◽  
Approximate Dynamic Programming ◽  
Capacity Allocation ◽  
Access Time ◽  
Programming Approach ◽  
Planning Problem ◽  
Dynamic Programming Approach ◽  
Negative Effect ◽  
Long Access

AbstractWe study an online capacity planning problem in which arriving patients require a series of appointments at several departments, within a certain access time target.This research is motivated by a study of rehabilitation planning practices at the Sint Maartenskliniek hospital (the Netherlands). In practice, the prescribed treatments and activities are typically booked starting in the first available week, leaving no space for urgent patients who require a series of appointments at a short notice. This leads to the rescheduling of appointments or long access times for urgent patients, which has a negative effect on the quality of care and on patient satisfaction.We propose an approach for allocating capacity to patients at the moment of their arrival, in such a way that the total number of requests booked within their corresponding access time targets is maximized. The model considers online decision making regarding multi-priority, multi-appointment, and multi-resource capacity allocation. We formulate this problem as a Markov decision process (MDP) that takes into account the current patient schedule, and future arrivals. We develop an approximate dynamic programming (ADP) algorithm to obtain approximate optimal capacity allocation policies. We provide insights into the characteristics of the optimal policies and evaluate the performance of the resulting policies using simulation.

Time-Jerk Synthetic Optimal Trajectory Planning of Robot Using Strength Pareto Evolutionary Algorithm

2010 ◽  
Vol 108-111 ◽  
pp. 1141-1146
Author(s):  
Jie Yan ◽  
Dao Xiong Gong
Keyword(s):  
Evolutionary Algorithm ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
High Speed ◽  
Mathematic Model ◽  
Stair Climbing ◽  
Planning Problem ◽  
Hexapod Robot ◽  
Strength Pareto Evolutionary Algorithm ◽  
Optimal Trajectory Planning

The Strength Pareto Evolutionary Algorithm (SPEA) is adopted to find time-jerk synthetic optimal trajectory of a hexapod robot in the joint space. In order to get the optimal trajectory, cubic splines are employed and derived under the constraint condition of via points to assure overall continuity of velocity and acceleration. Taken both the execution time and minimax approach of jerk as objectives, and expressed the kinematics constraints as upper bounds on the absolute values of velocity and acceleration, the mathematic model of time-jerk synthetic optimal trajectory planning is built. Finally, SPEA is adopted to optimize the stair-climbing trajectory of a hexapod robot, the simulation results show that this method can solve the trajectory planning problem effectively, and the stair-climbing trajectory can meet the contradictory objective functions of high speed and low robot vibration well.

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