| dc.description.abstract | When attempting to plan for an interaction between two robots there are many factors that compound its complexity, including the number of joints each robot has, causes for collision, power usage, placement of the end effectors, and others. These factors compound themselves as the robots involved increase in joints, there is an increase in obstacles, or more robots are added to the system. In an effort to devise an algorithm that provides a fast and effective solution to these types of problems, previous work has been done on Reachable Volumes and Interaction Templates, algorithms that serve to reduce the processing time for high degrees-of-freedom (dof) robots with stringent constraints, and to reduce the processing time for certain interactions between two or more systems of robots, respectively. Reachable Volumes uses the volumes that each joint of the robot can occupy, and by choosing points within these volumes it can solve for a configuration at a given end effector position. This enables a quick way to evaluate a configuration for a high dof robot as well as providing a means of avoiding collisions with obstacles by simply sampling the volumes around the joints in areas not occupied by the obstacles. Additionally, another strength of Reachable Volumes is it provides the ability to precisely place the end effector at a desired location, which other motion planning algorithms struggle with. Interaction Templates can be used to "template" or formulate an interaction such as a handoff that can be applied to a "roadmap" or a collection of points that make up the movements of a manipulator in configuration space. In doing so, Interaction Templates can make complex and processing expensive tasks such as calculating for a handoff interaction much more efficient. The work below begins to integrate elements from the Reachable Volumes algorithm into Interaction Templates, which speeds up several steps on the Interaction Templates Algorithm as well as makes it more effective for high dof robots or situations with a multitude of constraints. It additionally sets up a framework for more robots to be included in the algorithm. | |
