Fri, Sep 13, 2019 @ 01:00 PM - 02:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Pradeep Rajendran, AME Ph.D. candidate
Talk Title: Speeding Up Trajectory Planning for Autonomous Robots Operating in Complex Environments
Abstract: Advances in sensing and computing hardware have physically equipped robots to operate in complex environments. In many real-world settings, we desire robots to operate at a high-level of autonomy to reduce operating costs and manpower requirements. A high-level of autonomy can be achieved only when robots are able to plan missions and tasks themselves. Trajectory planning is a fundamental building block required to support high-level decision making in robots.
Trajectory planning for autonomous robots operating in complex environments is a challenging problem. The complexity of trajectory planning problems stems from the dimensionality of robot's state space, the complexity of the robot kinematic and dynamic model, the nature of environmental constraints (e.g., obstacles), task constraints (e.g., rules), the optimization objective function, and the planning-time requirements needed for deployment in the real world. Depending on the complexity, these problems can be solved by existing methods to produce feasible trajectories. But, in many practical applications (e.g., automated package delivery), computing a feasible trajectory alone is not enough. The quality of the computed trajectory is also important. However, in many cases, computing truly optimal trajectories is computationally intensive and thus, very time-consuming. As a result, existing methods do not satisfy planning-time constraints required by the application while maintaining optimality. We need a method that produces high-quality trajectories and at the same time produce those trajectories quickly. Anytime methods handle exactly this problem. However, these methods produce high-quality trajectories quickly only when good heuristics are used.
This work focuses on techniques for anytime algorithms that speed up trajectory planning for autonomous robots in complex environments. It is anticipated that the methodology presented in this work will be applicable to mobile robots operating in an outdoor setting such as uneven terrain, water bodies. In such settings, the speed-up techniques will allow the robot to quickly react to the environment and perform tasks safely. Depending on the application domain, this will also serve as an enabling technology for more advanced services. Many industrial processes are currently use high degree-of-freedom manipulators that are manually programmed by a human operator. Methods presented in this work can greatly simplify workflows related to manipulators and improve manufacturing throughput.
Host: SK Gupta
Audiences: Everyone Is Invited
Contact: SK Gupta