Trust-based mixed-initiative teleoperation of mobile robots

Author(s):  
H. Saeidi ◽  
F. McLane ◽  
B. Sadrfaidpour ◽  
E. Sand ◽  
S. Fu ◽  
...  
2021 ◽  
Vol 10 (4) ◽  
pp. 1-34
Author(s):  
Manolis Chiou ◽  
Nick Hawes ◽  
Rustam Stolkin

This article 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. Last, 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.


2012 ◽  
Vol 132 (3) ◽  
pp. 381-388
Author(s):  
Takaaki Imaizumi ◽  
Hiroyuki Murakami ◽  
Yutaka Uchimura

2006 ◽  
Vol 65 (3) ◽  
pp. 229-241
Author(s):  
S. F. Yatsun ◽  
F. K. Freire ◽  
V. S. Dyshenko ◽  
O. A. Shadrina
Keyword(s):  

2019 ◽  
Author(s):  
Abhishek Verma ◽  
Virender Ranga

Relay node placement in wireless sensor networks for constrained environment is a critical task due to various unavoidable constraints. One of the most important constraints is unpredictable obstacles. Handling obstacles during relay node placement is complicated because of complexity involved to estimate the shape and size of obstacles. This paper presents an Obstacle-resistant relay node placement strategy (ORRNP). The proposed solution not only handles the obstacles but also estimates best locations for relay node placement in the network. It also does not involve any additional hardware (mobile robots) to estimate node locations thus can significantly reduce the deployment costs. Simulation results show the effectiveness of our proposed approach.


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