|Title||Shared Planning and Control for Mobile Robots with Integral Haptic Feedback|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Masone, C, Mohammadi, M, Robuffo Giordano, P, Franchi, A|
|Journal||The International Journal of Robotics Research|
|Keywords||Aerial Robotics, Optimal Trajectory Planning|
This paper presents a novel bilateral shared framework for online trajectory generation for mobile robots. The robot navigates along a dynamic path, represented as a B-spline, whose parameters are jointly controlled by a human supervisor and by an autonomous algorithm. The human steers the reference (ideal) path by acting on the path parameters which are also affected, at the same time, by the autonomous algorithm in order to ensure: i) collision avoidance, ii) path regularity and iii) proximity to some points of interest. These goals are achieved by combining a gradient descent-like control action with an automatic algorithm that re-initializes the traveled path (replanning) in cluttered environments in order to mitigate the effects of local minima. The control actions of both the human and the autonomous algorithm are fused via a filter that preserves a set of local geometrical properties of the path in order to ease the tracking task of the mobile robot. The bilateral component of the interaction is implemented via a force feedback that accounts for both human and autonomous control actions along the whole path, thus providing information about the mismatch between the reference and traveled path in an integral sense. The proposed framework is validated by means of realistic simulations and actual experiments deploying a quadrotor UAV supervised by a human operator acting via a force-feedback haptic interface. Finally, a user study is presented in order to validate the effectiveness of the proposed framework and the usefulness of the provided force cues.