A real-time motion planning algorithm for a hyper-redundant set of mechanisms

Abstract

ABSTRACT. We introduce a novel probabilistic algorithm (CPRM) for real-time motion planning in the configuration space C. Our algorithm differs from a Probabilistic Road Map algorithm (PRM) in the motion between a pair of anchoring points (local planner) which takes place on the boundary of the obstacle subspace O. We define a varying potential field f on ∂O as a Morse function and follow ∇f . We then exemplify our algorithm on a redundant worm climbing robot with n degrees of freedom and compare our algorithm running results with those of PRM.

An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting

“…There are several path planning algorithms developed for robotics systems, such as grid-based search algorithms (assumes every point/object is covered in a grid configuration [44,45]), interval-based search algorithms (generates paving to cover an entire configuration space instead of grid [44]), geometric algorithms (find safe path from the start to goal initially [46]), reward-based algorithms (a robot tries to take a path, and it is rewarded positively if successful and negatively if otherwise [47]), artificial potential fields algorithms (robot is modeled to be attracted to positive path and repelled by obstacles [48]), and sampling-based algorithms (path is found from the roadmap spaces of the configuration space). Each of the algorithms has potential use, and some are just classic methods like grid-based algorithms [49]. However, the most advanced methods are sampling-based algorithms, as they attain considerably better performance in high-dimensional spaces using a large degree of freedom.…”

Minimally actuated hyper-redundant robots: Motion planning methods based on fractals and self-organizing systems

“…The robot is shown in Figure 1, while a detailed view of each link and the mobile actuator is shown in Figure 2. A more in-depth description and motivation for the MASR mechanism is provided by Shvalb et al 19 For simplicity, we assume that each link is of uniform length L. The angle between the i-1th and ith serial link is denoted by q i (see Figure 1).…”

“…The total time t total required for the robot to reach a goal is thus comprised of the times required to rotate each joint plus the times required to traverse the actuator from one link to another plus a certain interruption delay between the The mobile actuator that travels upon the links. 19 translation and rotation. The latter two are a consumption of time unique to the MASR robot, and it is the price we pay for using less actuators than joints-there must be a "timeshare" of the actuator between the links.…”

Minimally actuated serial robot

“…In other words, if the absolute deviation of each angle of the MASR from the fully actuated robot is less than or equal to δ, xe is the endpoint of the MASR, and xe0 is the endpoint of the corresponding fully actuated robot, then what is (12) where f(δ) is an explicit formula relating the angular deviation δ to the 2-norm of the endpoint deviation? To calculate this dependence, we rewrite the position of the endpoint by combing Equations (1) and (2) (13) where αi is the orientation of the ith joint of the MASR and αi of the fully actuated robot. Using Equation (13) to express the error norm between the two endpoints yields: (14) By making use of the trigonometric identities (15) the terms inside the root symbol of Equation (14) become…”

“…Many recent works have addressed obstacle avoidance schemes for hyper redundant robots. State-of-the-art approaches including genetic algorithms [10] [11], variational methods [12], and probabilistic roadmaps [13] are used to plan the motions of the robots. There is a continuous progress in reducing the planning time and improving their capability in real life scenarios such as robotic surgery, agriculture and search and rescue.…”