An Intention Guided Hierarchical Framework for Trajectory-based Teleoperation of Mobile Robots

In human-in-the-loop navigation, the operator’s intention is to locally avoid obstacles while planning long-horizon paths in order to complete the navigation task. We propose a hierarchical teleoperation framework that captures these characteristics of intention, and generates trajectories that are locally safe and follow the operator’s global plan. The hierarchical teleoperation framework consists of 1) a global path which encapsulates the intended direction of the operator, 2) local trajectories that circumvent obstacles near the vehicle’s vicinity while following the global path, and 3) safety monitoring to avoid possible imminent collisions. By removing the operator from providing dynamic-level control inputs and instead having inputs inform trajectory generation, we show a significant reduction of the operator’s engagement while maintaining smooth performance.We showcase hierarchical teleoperation in navigation tasks in a random forest environment and a high-clutter warehouse characterized by narrow gaps and dense obstacles. With our method, we maintain consistent high speed throughout the task with smooth jerk profiles, decreased time to completion, and significantly reduced operator engagement.

[1]  Takeo Kanade,et al.  Efficient Two-phase 3D Motion Planning for Small Fixed-wing UAVs , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[2]  H. Mannila,et al.  Computing Discrete Fréchet Distance ∗ , 1994 .

[3]  Ross A. Knepper,et al.  Differentially constrained mobile robot motion planning in state lattices , 2009, J. Field Robotics.

[4]  Maxim Likhachev,et al.  Motion planning in urban environments , 2008, J. Field Robotics.

[5]  Sven Behnke,et al.  Hierarchical Planning with 3 D Local Multiresolution Obstacle Avoidance for Micro Aerial Vehicles , 2014 .

[6]  Rafael Sanz,et al.  Deliberative On-Line Local Path Planning for Autonomous Mobile Robots , 2003, J. Intell. Robotic Syst..

[7]  Xuning Yang,et al.  Fast and Agile Vision-Based Flight with Teleoperation and Collision Avoidance on a Multirotor , 2018, ISER.

[8]  Boris Aronov,et al.  Fréchet Distance for Curves, Revisited , 2006, ESA.

[9]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  Sven Behnke,et al.  Multimodal obstacle detection and collision avoidance for micro aerial vehicles , 2013, 2013 European Conference on Mobile Robots.

[11]  Assisted Mobile Robot Teleoperation with Intent-aligned Trajectories via Biased Incremental Action Sampling , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[12]  Martial Hebert,et al.  A Navigation System for Goal Acquisition in Unknown Environments , 1997 .

[13]  Yann LeCun,et al.  A multirange architecture for collision‐free off‐road robot navigation , 2009, J. Field Robotics.