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Control systems driven by voice recognition software have been implemented before but lacked the context driven approach to generate relevant responses and actions. A partially voice activated control system for mobile robotics is presented that allows an autonomous robot to interact with people and the environment in a meaningful way, while dynami...
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Citations
... Voice-operated control have been applied to different applications from medical field like surgical devices (Reichenspurner et al., 1999) to pc functions such as cursor movement (Harada et al., 2008), keyboard (Manaris et al., 2001) and in home applications through sound activated switches and painting (Harada et al., 2007). Some attempts was made to tackle issues related use of voice-control such as; continuous control (Igarashi and Hughes, 2001) traing efforts for voice recognition (Smith et al., 2010), noisy environment (Wijekoon et al., 2004). Acoustic phonetic parameters like pitch, loudness (House et al., 2009), vowel quality can be used to control the motion (Bilmes et al., 2005). ...
A visitor-following method that guides visitors as they move around was successfully developed without changing the structure of the waypoint navigation system. We previously developed a guidance robot, “EM-Ro,” to provide guidance services at the ECO35 Muffler Museum, and used the waypoint navigation system to implement a visitor-escort method along a predetermined route. With this visitor-following method, EM-Ro was able to follow a target visitor along visitor-derived waypoints, which were estimated using 2D LiDAR. Thus, the proposed navigation system for the guidance robot provides both visitor-escort and visitor-following guidance services. Using the same waypoint navigation system, it was possible to seamlessly switch between visitor-escort and visitor-following guidance. Switching between prepared or visitor-derived waypoints can make a visitor choose the preferred guidance method. Visitors can switch the guidance method anytime by providing EM-Ro requests from the remote controller. In addition, a guest redetecting method was developed when EM-Ro lost guests. The experimental results at the Muffler Museum showed that both visitor-escort and visitor-following driving by the EM-Ro were successfully demonstrated while guiding guests in the facility.
Our institution has on-going research projects which utilize autonomous mobile robots in a variety of settings. These robots navigate and interact with humans and their environment. As part of this effort a framework to integrate the navigational operation and the speech interaction to react to contextual stimuli is provided. This framework provides a system which is easy to configure and modify. The basis of this framework blends the rationale of human nature with the interpretation of sensor inputs. This combination of real-time and environmental information is at the core of having situational awareness. Context-based mapping allows the system to learn an environmental context and how to identify it from real-time interaction. Context-based mapping techniques link data prioritized by contextual value to physical locations on a visual or representative map. This system categorizes objects and events in an adaptive way. By determining the appropriate behavior in a given situation, a mobile robot uses only the relevant knowledge and data. This information is stored to allow both historical and real-time data to be used as appropriate. This approach allows the robot to access the previously collected data for statistical reference. As data are collected from various sensory inputs, the weighted contribution in that context is determined. This research examined the deployment of an autonomous mobile robot. The robot was able to function in the environment, which included both indoor and outdoor settings. Speech was used for input and as response explanations by the robot. The robot was trained initially in a supervised mode, but after the heuristics and adjustments had been reached, the robot was able to balance the sensors appropriately and learn without supervision. The result was a robot that could navigate autonomously and respond to the environment appropriately. Experiments were performed to demonstrate the ability of the robot to function effectively in indoor- and outdoor environments and transition between them. The robot was also able to create a defined signature for a location using sensor information. After this training, the robot was able to exhibit situational awareness in dynamic environments, answering numerous questions regarding the state of the surrounding environment.
