2 research outputs found
VFH+ based shared control for remotely operated mobile robots
This paper addresses the problem of safe and efficient navigation in remotely
controlled robots operating in hazardous and unstructured environments; or
conducting other remote robotic tasks. A shared control method is presented
which blends the commands from a VFH+ obstacle avoidance navigation module with
the teleoperation commands provided by an operator via a joypad. The presented
approach offers several advantages such as flexibility allowing for a
straightforward adaptation of the controller's behaviour and easy integration
with variable autonomy systems; as well as the ability to cope with dynamic
environments. The advantages of the presented controller are demonstrated by an
experimental evaluation in a disaster response scenario. More specifically,
presented evidence show a clear performance increase in terms of safety and
task completion time compared to a pure teleoperation approach, as well as an
ability to cope with previously unobserved obstacles.Comment: 8 pages,6 figure
Mixed-initiative variable autonomy for remotely operated mobile robots
This paper presents an Expert-guided Mixed-Initiative Control Switcher
(EMICS) for remotely operated mobile robots. The EMICS enables switching
between different levels of autonomy during task execution initiated by either
the human operator and/or the EMICS. The EMICS is evaluated in two disaster
response inspired experiments, one with a simulated robot and test arena, and
one with a real robot in a realistic environment.
Analyses from the two experiments provide evidence that: a) Human-Initiative
(HI) systems outperform systems with single modes of operation, such as pure
teleoperation, in navigation tasks; b) in the context of the simulated robot
experiment, Mixed-Initiative (MI) systems provide improved performance in
navigation tasks, improved operator performance in cognitive demanding
secondary tasks, and improved operator workload compared to HI. Results also
reinforce previous human-robot interaction evidence regarding the importance of
the operator's personality traits and their trust in the autonomous system.
Lastly, our experiment on a physical robot provides empirical evidence that
identify two major challenges for MI control: a) the design of context-aware MI
control systems; and b) the conflict for control between the robot's MI control
system and the operator. Insights regarding these challenges are discussed and
ways to tackle them are proposed.Comment: Submitted for journal publication, under revie