Path Planning For Redundant Manipulators Research Articles

Optimal randomized path planning for redundant manipulators based on Memory-Goal-Biasing

Planning path rapidly and optimally is one of the key technologies for industrial manipulators. A novel method based on Memory-Goal-Biasing–Rapidly-exploring Random Tree is proposed to solve high-dimensional manipulation planning more rapidly and optimally. The tree extension of Memory-Goal-Biasing–Rapidly-exploring Random Tree can be divided into random extension and goal extension. In the goal extension, the nodes extended to the goal are recorded in a memory, and then the node closest to the goal is selected in the search tree excepting the nodes in the memory for overcoming the local minimum. In order to check collisions efficiently, the manipulator is simplified into several key points, and the obstacle area is appropriately enlarged for safety. Taking the redundant manipulator of Baxter robot as an example, the proposed algorithm is verified through MoveIt! software. The results show that Memory-Goal-Biasing–Rapidly-exploring Random Tree only takes a few seconds for the path planning of the redundant manipulator in some complex environments, and within an acceptable time, its optimization performance is better than that of traditional optimal method in terms of the obtained path costs and the corresponding standard deviation.

RoboKol: A computer program for path planning for redundant and mobile robots

AbstractRedundant manipulators are defined as having an infinite number of solutions to their joint variables. Their many degrees of freedom make them able to determine their configurations to reach the goal point while avoiding obstacles in the workspace. A computer program we named it RoboKol is introduced in this paper, which performs path planning for redundant manipulators and mobile robots using potential field based algorithms. It has been developed in C++ for Windows platforms. Through a friendly user interface, the user can interact with the program and can perform a variety of operations such as drawing obstacles and robots on the screen, obtaining two‐ and three‐dimensional images of the potential field and performing robot simulations. Although RoboKol has originally been developed for research purposes, it is a convenient tool to teach potential fields, path planning for redundant manipulators and mobile robots in engineering education. Comput Appl Eng Educ 14: 198–210, 2006; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20078

The beam analysis algorithm for path planning for redundant manipulators

An algorithm for path planning for redundant manipulators is presented in this paper. The algorithm uses harmonic potential fields defined globally in W-space (work space) for both path planning and obstacle avoidance. Although paths generated by harmonic potential fields are collision free for point robots, this is not always the case for manipulators when especially tight manoeuvring is required. To enhance collision avoidance ability of redundant manipulators, the beam analysis algorithm is proposed. The algorithm sends beams along the path generated for point robots to determine virtual obstacle points where collision with obstacle is likely to occur. The potential field is then regenerated to include these virtual obstacle points. Besides, the interaction between manipulator links and the potential field is accomplished by the control points situated on only proximal ends of the links. The virtual obstacle points and selected control points allow the manipulator to achieve tight manoeuvring in W-spaces cluttered with many obstacles. The improvement in performance is also clearly indicated by a benchmark scheme that compares the algorithms by means of the complexity of the environment with respect to link lengths of redundant manipulators. Furthermore, the beam analysis algorithm readily produces safer paths for mobile robots, which does not suffer too far or too close problems. Examples are included to demonstrate these features of the algorithm.

Path Planning for Redundant Manipulators with Load Distribution Consideration

This paper presents a novel method for path planning of redundant manipulators. The idea is to use load distribution as an objective function for resolving kinematic redundancy. The method is based on imposing a convenient relation among joint torques as a dynamic constraint equation to system. An algorithm for path planning of redundant manipulators subject to dynamic constraints, and an algorithm for finding a starting point with good load distribution is presented. These two algorithms are combined to develop the main algorithm, which can fmd a good starting point and generates a path in joint space such that the required load distribution objective is satisfied. The results for path plarming of a 3-DOF planar manipulator using this method are presented.

Generation of adjacent configurations for a collision-free path planning of manipulators

SUMMARYIn this paper an algorithm is proposed for the problem of path planning of redundant manipulators among obstacles by using a suitable formulation for robot configurations and path strategy. In particular robotic manipulators have been modelled by using reference points on the kinematic chain and their Cartesian coordinates description. The path planning has been formulated as an optimization problem for the determination of adjacent configurations and the path among obstacles with minimum manipulator displacement. The fully Cartesian coordinates description has been useful for the economy of the numerical procedure and for the constraints formulation of link interference and obstacles avoidance constraints. Some examples are reported which prove the practical feasibility of the path planning procedure, and the numerical results have been tested as applicable to industrial robots through easy programming because of the concept of adjacent configurations.

A global approach to path planning for redundant manipulators

A global approach to path planning for redundant manipulators