Integrated motion planning and control for graceful balancing mobile robots

Abstract

Abstract-This paper presents an integrated motion planning and control framework that enables balancing mobile robots to gracefully navigate human environments. A palette of controllers called motion policies is designed such that balancing mobile robots can achieve fast, graceful motions in small, collision-free domains of the position space. The domains determine the validity of a motion policy at any point in the robot's position state space. An automatic instantiation procedure that generates a motion policy library by deploying motion policies from a palette on a map of the environment is presented. A gracefully prepares relationship that guarantees valid compositions of motion policies to produce overall graceful motion is introduced. A directed graph called the gracefully prepares graph is used to represent all valid compositions of motion policies in the motion policy library. The navigation tasks are achieved by planning in the space of these gracefully composable motion policies. In this work, Dijsktra's algorithm is used to generate a single-goal optimal motion policy tree, and its variant is used to rapidly replan the optimal motion policy tree in the presence of dynamic obstacles. A hybrid controller is used as a supervisory controller to ensure successful execution of motion policies and also successful switching between them.The integrated motion planning and control framework presented in this paper was experimentally tested on the ballbot, a human-sized dynamically stable mobile robot that balances on a single ball. The results of successful experimental testing of two navigation tasks, namely, pointpoint and surveillance motions are presented. Additional experimental results that validate the framework's capability to handle disturbances and rapidly replan in the presence of dynamic obstacles are also presented.

Shape space planner for shape-accelerated balancing mobile robots

“…One needs to evaluate the robustness of the proposed shape trajectory planner and the control architecture to large disturbances. A navigation framework that uses the shape trajectory planner and the control architecture to achieve desired navigation tasks has been presented in Nagarajan et al (2013). Several approaches towards automatically choosing weight matrices for a given navigation task can also be explored.…”

Safe Adaptive Switching among Dynamical Movement Primitives: Application to 3D Limit-Cycle Walkers

“…Later work in [6] provided a computationally tractable approach to estimate the Lyapunov funnels construction of [5] based on Sumof-Squares (SoS) programming [10]. This method and its extensions have been experimentally successful for planning motions of a wheeled robot [11], ball-bot [12], and a fixedwing airplane [13]. Other methods address composability of dynamic primitives, capturing the associated constraints in the form of maneuver [14] or timed [15] automata.…”