The program is planned as the initial degree introduction to robot motion planning for teachers, students and industry individuals. Historically, this motion planning and path planning is for algorithm design which can get collision-free ways to take their robot from the starting point to its destination point. Because of current interests in creating a system of autonomous robotics, the course has become incredibly wide. It encloses not only conventional regions of collision-free ways but warehouse automation, automatic assembly, robotic surgery, many robot alliances, etc. The course will also cover the basic concepts and mathematics needed to learn, design, and analyze the algorithms needed for the motion planning of consecutive mobile robots and robotic arms. After studying this course, they can take highly advanced topics or courses in various focused regions, such as the role of AI in motion planning, probabilistic motion planning, uncrewed vehicles, etc. Also, teachers can utilize this course to point out the basis of other courses, which involve mobile robots, AI, manufacturing automation, computer illusion applications, etc.
Suppose a robot works to compile products. This product is designed using a CAD network, k, and the required details about the composing parts of this product are available. In which manner does the robot compile these products? What trajectories does it enforce to avoid any collision in the path? Which sensing undertakings does it conduct to counsel its motion and do the various tasks despite a few uncertainties in the locations and shapes of the parts? Motion planning aims to provide reasonable answers to such questions.
Although the techniques of motion planning were developed to develop robots having motion autonomy, mobile robots guide in construction; however, after some time, these techniques were applied and more developed in several contexts, like virtual prototyping of recent products, design for servicing and manufacturing, plant supervision, medical surgeries, character animation, code checking in building, layout design of pipes, design of rational drugs.
Thus, motion planning can be described as the motions of virtual or real objects, one or several in number, in some work area to attain a specified tasked goal, such as:
• Moving to a particular point in a provided environment
• Making a map of an unknown environment
• Keeping some products with their separate ones
• Orienting some parts by pushing them.
Path planning is a primary component needed to resolve the bigger problems of various autonomous robot navigation. Various autonomous courses are there which solve such problems very easily. In such courses, you will get various concepts about the greatly utilized path planning algorithms. You will use theories to make a practical by running the appropriate code exercises and simulations in ROS.
At the final touch of such courses, you will have to understand various approaches that can be used to eliminate the problems of global path planning. Moreover, you will explain and understand the differences between them and the various drawbacks and advantages of each other. Lastly, you have achieved good practical knowledge and experience by enforcing these procedures.