Variational calculus and optimal control (2nd ed.): optimization with elementary convexity
Variational calculus and optimal control (2nd ed.): optimization with elementary convexity
Trust-region methods
Robot Motion Planning
Planning Algorithms
Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots
International Journal of Robotics Research
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
Practical Methods for Optimal Control and Estimation Using Nonlinear Programming
Practical Methods for Optimal Control and Estimation Using Nonlinear Programming
Smooth motion generation for unicycle mobile robots via dynamic path inversion
IEEE Transactions on Robotics
From Reeds and Shepp's to continuous-curvature paths
IEEE Transactions on Robotics
-Splines for the Smooth Path Generation of Wheeled Mobile Robots
IEEE Transactions on Robotics
An Optimality Principle Governing Human Walking
IEEE Transactions on Robotics
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Assistive mobile robots that can navigate autonomously can greatly benefit people with mobility impairments. Since an assistive mobile robot transports a human user from one place to another, its motion should be comfortable for human users. Moreover, it should be possible for users to customize the motion according to their comfort. While there exists a large body of work on motion planning for mobile robots, very little attention has been paid to characterizing comfort and planning comfortable trajectories. In this paper, we first characterize comfortable motion by formulating a measure of discomfort as a weighted sum of the total travel time and time integrals of various kinematic quantities. We then present a method for factoring the weights such that once a user has customized the weights for one task, the same choice of weights leads to similar average value of the discomfort measure in other tasks. We seek trajectories that minimize the discomfort and satisfy boundary conditions on pose, velocity and acceleration. Such a problem can naturally be formulated as a variational optimization problem. Unlike previous work, we present a comprehensive formulation that allows the travel time to be unspecified and includes boundary conditions on position, orientation, velocity and acceleration. This makes the formulation very general as it can be used to compute trajectories for various kinds of tasks, such as starting from rest, coming to rest, moving from one specified velocity to another, arriving at a goal with a specified orientation etc. Finally, we present a fast and robust numerical method for solving the minimization problem.