Gestures for Manually Controlling a Helping Hand Robot

Helping hand robots have been the focus of a number of studies and have high potential in modern manufacturing processes and for use in daily living. As helping hand robots interact closely with users, it is important to find natural and intuitive user interfaces for interacting with the robots in various situations. This study describes a set of gestures for interacting with and controlling helping hand robots in situations in which users need to manually control the robot but both hands are not available, for example, when users are holding tools or objects in their hands. The gestures are derived from an experimental study that asked participants for gestures suitable for controlling primitive robot motions. The selected gestures can be used to control translation and orientation of an end effector of a helping hand robot when one or both hands are engaged with tasks. As an example for validating the proposed gestures, we implemented a helping hand robot system to perform a soldering task

Using Gestures to Resolve Lexical Ambiguity in Storytelling with Humanoid Robots

Gestures that co-occur with speech are a fundamental component of communication. Prior research with children suggests that gestures may help them to resolve certain forms of lexical ambiguity, including homophones. To test this idea in the context of human-robot interaction, the effects of iconic and deictic gestures on the understanding of homophones was assessed in an experiment where a humanoid robot told a short story containing pairs of homophones to small groups of young participants, accompanied by either expressive gestures or no gestures. Both groups of subjects completed a pretest and post-test to measure their ability to discriminate between pairs of homophones and we calculated aggregated precision. The results show that the use of iconic and deictic gestures aids in general understanding of homophones, providing additional evidence for the importance of gesture to the development of children’s language and communication skills

SARSCEST (human factors)

People interact with the processes and products of contemporary technology. Individuals are affected by these in various ways and individuals shape them. Such interactions come under the label 'human factors'. To expand the understanding of those to whom the term is relatively unfamiliar, its domain includes both an applied science and applications of knowledge. It means both research and development, with implications of research both for basic science and for development. It encompasses not only design and testing but also training and personnel requirements, even though some unwisely try to split these apart both by name and institutionally. The territory includes more than performance at work, though concentration on that aspect, epitomized in the derivation of the term ergonomics, has overshadowed human factors interest in interactions between technology and the home, health, safety, consumers, children and later life, the handicapped, sports and recreation education, and travel. Two aspects of technology considered most significant for work performance, systems and automation, and several approaches to these, are discussed

Interactive spaces for children: gesture elicitation for controlling ground mini-robots

[EN] Interactive spaces for education are emerging as a mechanism for fostering children's natural ways of learning by means of play and exploration in physical spaces. The advanced interactive modalities and devices for such environments need to be both motivating and intuitive for children. Among the wide variety of interactive mechanisms, robots have been a popular research topic in the context of educational tools due to their attractiveness for children. However, few studies have focused on how children would naturally interact and explore interactive environments with robots. While there is abundant research on full-body interaction and intuitive manipulation of robots by adults, no similar research has been done with children. This paper therefore describes a gesture elicitation study that identified the preferred gestures and body language communication used by children to control ground robots. The results of the elicitation study were used to define a gestural language that covers the different preferences of the gestures by age group and gender, with a good acceptance rate in the 6-12 age range. The study also revealed interactive spaces with robots using body gestures as motivating and promising scenarios for collaborative or remote learning activities.This work is funded by the European Development Regional Fund (EDRF-FEDER) and supported by the Spanish MINECO (TIN2014-60077-R). The work of Patricia Pons is supported by a national grant from the Spanish MECD (FPU13/03831). Special thanks are due to the children and teachers of the Col-legi Public Vicente Gaos for their valuable collaboration and dedication.Pons Tomás, P.; Jaén Martínez, FJ. (2020). Interactive spaces for children: gesture elicitation for controlling ground mini-robots. Journal of Ambient Intelligence and Humanized Computing. 11(6):2467-2488. https://doi.org/10.1007/s12652-019-01290-6S24672488116Alborzi H, Hammer J, Kruskal A et al (2000) Designing StoryRooms: interactive storytelling spaces for children. In: Proceedings of the conference on designing interactive systems processes, practices, methods, and techniques—DIS’00. ACM Press, New York, pp 95–104Antle AN, Corness G, Droumeva M (2009) What the body knows: exploring the benefits of embodied metaphors in hybrid physical digital environments. Interact Comput 21:66–75. https://doi.org/10.1016/j.intcom.2008.10.005Belpaeme T, Baxter PE, Read R et al (2013) Multimodal child–robot interaction: building social bonds. J Human-Robot Interact 1:33–53. https://doi.org/10.5898/JHRI.1.2.BelpaemeBenko H, Wilson AD, Zannier F, Benko H (2014) Dyadic projected spatial augmented reality. In: Proceedings of the 27th annual ACM symposium on user interface software and technology—UIST’14, pp 645–655Bobick AF, Intille SS, Davis JW et al (1999) The KidsRoom: a perceptually-based interactive and immersive story environment. Presence Teleoper Virtual Environ 8:367–391. https://doi.org/10.1162/105474699566297Bonarini A, Clasadonte F, Garzotto F, Gelsomini M (2015) Blending robots and full-body interaction with large screens for children with intellectual disability. In: Proceedings of the 14th international conference on interaction design and children—IDC’15. ACM Press, New York, pp 351–354Cauchard JR, E JL, Zhai KY, Landay JA (2015) Drone & me: an exploration into natural human–drone interaction. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing—UbiComp’15. ACM Press, New York, pp 361–365Connell S, Kuo P-Y, Liu L, Piper AM (2013) A Wizard-of-Oz elicitation study examining child-defined gestures with a whole-body interface. In: Proceedings of the 12th international conference on interaction design and children—IDC’13. ACM Press, New York, pp 277–280Derboven J, Van Mechelen M, Slegers K (2015) Multimodal analysis in participatory design with children. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems—CHI’15. ACM Press, New York, pp 2825–2828Dong H, Danesh A, Figueroa N, El Saddik A (2015) An elicitation study on gesture preferences and memorability toward a practical hand-gesture vocabulary for smart televisions. IEEE Access 3:543–555. https://doi.org/10.1109/ACCESS.2015.2432679Druin A (1999) Cooperative inquiry: developing new technologies for children with children. In: Proceedings of the SIGCHI conference on human factors computer system CHI is limit—CHI’99, vol 14, pp 592–599. https://doi.org/10.1145/302979.303166Druin A (2002) The role of children in the design of new technology. Behav Inf Technol 21:1–25. https://doi.org/10.1080/01449290110108659Druin A, Bederson B, Boltman A et al (1999) Children as our technology design partners. In: Druin A (ed) The design of children’s technology. Morgan Kaufman, San Francisco, pp 51–72Epps J, Lichman S, Wu M (2006) A study of hand shape use in tabletop gesture interaction. CHI’06 extended abstracts on human factors in computing systems—CHI EA’06. ACM Press, New York, pp 748–753Fender AR, Benko H, Wilson A (2017) MeetAlive : room-scale omni-directional display system for multi-user content and control sharing. In: Proceedings of the 2017 ACM international conference on interactive surfaces and spaces, pp 106–115Fernandez RAS, Sanchez-Lopez JL, Sampedro C et al (2016) Natural user interfaces for human–drone multi-modal interaction. In: 2016 international conference on unmanned aircraft systems (ICUAS). IEEE, New York, pp 1013–1022Garcia-Sanjuan F, Jaen J, Nacher V, Catala A (2015) Design and evaluation of a tangible-mediated robot for kindergarten instruction. In: Proceedings of the 12th international conference on advances in computer entertainment technology—ACE’15. ACM Press, New York, pp 1–11Garcia-Sanjuan F, Jaen J, Jurdi S (2016) Towards encouraging communication in hospitalized children through multi-tablet activities. In: Proceedings of the XVII international conference on human computer interaction, pp 29.1–29.4Gindling J, Ioannidou A, Loh J et al (1995) LEGOsheets: a rule-based programming, simulation and manipulation environment for the LEGO programmable brick. In: Proceedings of symposium on visual languages. IEEE Computer Society Press, New York, pp 172–179Gonzalez B, Borland J, Geraghty K (2009) Whole body interaction for child-centered multimodal language learning. In: Proceedings of the 2nd workshop on child, computer and interaction—WOCCI’09. ACM Press, New York, pp 1–5Grønbæk K, Iversen OS, Kortbek KJ et al (2007) Interactive floor support for kinesthetic interaction in children learning environments. In: Human–computer interaction—INTERACT 2007. Lecture notes in computer science, pp 361–375Guha ML, Druin A, Chipman G et al (2005) Working with young children as technology design partners. Commun ACM 48:39–42. https://doi.org/10.1145/1039539.1039567Hansen JP, Alapetite A, MacKenzie IS, Møllenbach E (2014) The use of gaze to control drones. In: Proceedings of the symposium on eye tracking research and applications—ETRA’14. ACM Press, New York, pp 27–34Henkemans OAB, Bierman BPB, Janssen J et al (2017) Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1. Int J Hum Comput Stud 106:63–76. https://doi.org/10.1016/j.ijhcs.2017.06.001Horn MS, Crouser RJ, Bers MU (2011) Tangible interaction and learning: the case for a hybrid approach. Pers Ubiquitous Comput 16:379–389. https://doi.org/10.1007/s00779-011-0404-2Hourcade JP (2015) Child computer interaction. CreateSpace Independent Publishing Platform, North CharlestonHöysniemi J, Hämäläinen P, Turkki L (2004) Wizard of Oz prototyping of computer vision based action games for children. Proceeding of the 2004 conference on interaction design and children building a community—IDC’04. ACM Press, New York, pp 27–34Höysniemi J, Hämäläinen P, Turkki L, Rouvi T (2005) Children’s intuitive gestures in vision-based action games. Commun ACM 48:44–50. https://doi.org/10.1145/1039539.1039568Hsiao H-S, Chen J-C (2016) Using a gesture interactive game-based learning approach to improve preschool children’s learning performance and motor skills. Comput Educ 95:151–162. https://doi.org/10.1016/j.compedu.2016.01.005Jokela T, Rezaei PP, Väänänen K (2016) Using elicitation studies to generate collocated interaction methods. In: Proceedings of the 18th international conference on human–computer interaction with mobile devices and services adjunct, pp 1129–1133. https://doi.org/10.1145/2957265.2962654Jones B, Benko H, Ofek E, Wilson AD (2013) IllumiRoom: peripheral projected illusions for interactive experiences. In: Proceedings of the SIGCHI conference on human factors in computing systems—CHI’13, pp 869–878Jones B, Shapira L, Sodhi R et al (2014) RoomAlive: magical experiences enabled by scalable, adaptive projector-camera units. In: Proceedings of the 27th annual ACM symposium on user interface software and technology—UIST’14, pp 637–644Kaminski M, Pellino T, Wish J (2002) Play and pets: the physical and emotional impact of child-life and pet therapy on hospitalized children. Child Heal Care 31:321–335. https://doi.org/10.1207/S15326888CHC3104_5Karam M, Schraefel MC (2005) A taxonomy of gestures in human computer interactions. In: Technical report in electronics and computer science, pp 1–45Kistler F, André E (2013) User-defined body gestures for an interactive storytelling scenario. Lect Notes Comput Sci (including subser Lect Notes Artif Intell Lect Notes Bioinform) 8118:264–281. https://doi.org/10.1007/978-3-642-40480-1_17Konda KR, Königs A, Schulz H, Schulz D (2012) Real time interaction with mobile robots using hand gestures. In: Proceedings of the seventh annual ACM/IEEE international conference on human–robot interaction—HRI’12. ACM Press, New York, pp 177–178Kray C, Nesbitt D, Dawson J, Rohs M (2010) User-defined gestures for connecting mobile phones, public displays, and tabletops. In: Proceedings of the 12th international conference on human computer interaction with mobile devices and services—MobileHCI’10. ACM Press, New York, pp 239–248Kurdyukova E, Redlin M, André E (2012) Studying user-defined iPad gestures for interaction in multi-display environment. In: Proceedings of the 2012 ACM international conference on intelligent user interfaces—IUI’12. ACM Press, New York, pp 93–96Lambert V, Coad J, Hicks P, Glacken M (2014) Social spaces for young children in hospital. Child Care Health Dev 40:195–204. https://doi.org/10.1111/cch.12016Lee S-S, Chae J, Kim H et al (2013) Towards more natural digital content manipulation via user freehand gestural interaction in a living room. In: Proceedings of the 2013 ACM international joint conference on pervasive and ubiquitous computing—UbiComp’13. ACM Press, New York, p 617Malinverni L, Mora-Guiard J, Pares N (2016) Towards methods for evaluating and communicating participatory design: a multimodal approach. Int J Hum Comput Stud 94:53–63. https://doi.org/10.1016/j.ijhcs.2016.03.004Mann HB, Whitney DR (1947) On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50–60. https://doi.org/10.1214/aoms/1177730491Marco J, Cerezo E, Baldassarri S et al (2009) Bringing tabletop technologies to kindergarten children. In: Proceedings of the 23rd British HCI Group annual conference on people and computers: celebrating people and technology, pp 103–111Michaud F, Caron S (2002) Roball, the rolling robot. Auton Robots 12:211–222. https://doi.org/10.1023/A:1014005728519Micire M, Desai M, Courtemanche A et al (2009) Analysis of natural gestures for controlling robot teams on multi-touch tabletop surfaces. In: Proceedings of the ACM international conference on interactive tabletops and surfaces—ITS’09. ACM Press, New York, pp 41–48Mora-Guiard J, Crowell C, Pares N, Heaton P (2016) Lands of fog: helping children with autism in social interaction through a full-body interactive experience. In: Proceedings of the 15th international conference on interaction design and children—IDC’16. ACM Press, New York, pp 262–274Morris MR (2012) Web on the wall: insights from a multimodal interaction elicitation study. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfaces. ACM Press, New York, pp 95–104Morris MR, Wobbrock JO, Wilson AD (2010) Understanding users’ preferences for surface gestures. Proc Graph Interface 2010:261–268Nacher V, Garcia-Sanjuan F, Jaen J (2016) Evaluating the usability of a tangible-mediated robot for kindergarten children instruction. In: 2016 IEEE 16th international conference on advanced learning technologies (ICALT). IEEE, New York, pp 130–132Nahapetyan VE, Khachumov VM (2015) Gesture recognition in the problem of contactless control of an unmanned aerial vehicle. Optoelectron Instrum Data Process 51:192–197. https://doi.org/10.3103/S8756699015020132Obaid M, Häring M, Kistler F et al (2012) User-defined body gestures for navigational control of a humanoid robot. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), pp 367–377Obaid M, Kistler F, Häring M et al (2014) A framework for user-defined body gestures to control a humanoid robot. Int J Soc Robot 6:383–396. https://doi.org/10.1007/s12369-014-0233-3Obaid M, Kistler F, Kasparavičiūtė G, et al (2016) How would you gesture navigate a drone?: a user-centered approach to control a drone. In: Proceedings of the 20th international academic Mindtrek conference—AcademicMindtrek’16. ACM Press, New York, pp 113–121Pares N, Soler M, Sanjurjo À et al (2005) Promotion of creative activity in children with severe autism through visuals in an interactive multisensory environment. In: Proceeding of the 2005 conference on interaction design and children—IDC’05. ACM Press, New York, pp 110–116Pfeil K, Koh SL, LaViola J (2013) Exploring 3D gesture metaphors for interaction with unmanned aerial vehicles. In: Proceedings of the 2013 international conference on intelligent user interfaces—IUI’13, pp 257–266. https://doi.org/10.1145/2449396.2449429Piaget J (1956) The child’s conception of space. Norton, New YorkPiaget J (1973) The child and reality: problems of genetic psychology. Grossman, New YorkPiumsomboon T, Clark A, Billinghurst M, Cockburn A (2013) User-defined gestures for augmented reality. CHI’13 extended abstracts on human factors in computing systems—CHI EA’13. ACM Press, New York, pp 955–960Pons P, Carrión A, Jaen J (2018) Remote interspecies interactions: improving humans and animals’ wellbeing through mobile playful spaces. Pervasive Mob Comput. https://doi.org/10.1016/j.pmcj.2018.12.003Puranam MB (2005) Towards full-body gesture analysis and recognition. University of Kentucky, LexingtonPyryeskin D, Hancock M, Hoey J (2012) Comparing elicited gestures to designer-created gestures for selection above a multitouch surface. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfaces—ITS’12. ACM Press, New York, pp 1–10Raffle HS, Parkes AJ, Ishii H (2004) Topobo: a constructive assembly system with kinetic memory. System 6:647–654. https://doi.org/10.1145/985692.985774Read JC, Markopoulos P (2013) Child–computer interaction. Int J Child-Comput Interact 1:2–6. https://doi.org/10.1016/j.ijcci.2012.09.001Read JC, Macfarlane S, Casey C (2002) Endurability, engagement and expectations: measuring children’s fun. In: Interaction design and children, pp 189–198Read JC, Markopoulos P, Parés N et al (2008) Child computer interaction. In: Proceeding of the 26th annual CHI conference extended abstracts on human factors in computing systems—CHI’08. ACM Press, New York, pp 2419–2422Robins B, Dautenhahn K (2014) Tactile interactions with a humanoid robot: novel play scenario implementations with children with autism. Int J Soc Robot 6:397–415. https://doi.org/10.1007/s12369-014-0228-0Robins B, Dautenhahn K, Te Boekhorst R, Nehaniv CL (2008) Behaviour delay and robot expressiveness in child–robot interactions: a user study on interaction kinesics. In: Proceedings of the 3rd ACMIEEE international conference on human robot interaction, pp 17–24. https://doi.org/10.1145/1349822.1349826Ruiz J, Li Y, Lank E (2011) User-defined motion gestures for mobile interaction. In: Proceedings of the 2011 annual conference on human factors in computing systems—CHI’11. ACM Press, New York, p 197Rust K, Malu M, Anthony L, Findlater L (2014) Understanding childdefined gestures and children’s mental models for touchscreen tabletop interaction. In: Proceedings of the 2014 conference on interaction design and children—IDC’14. ACM Press, New York, pp 201–204Salter T, Dautenhahn K, Te Boekhorst R (2006) Learning about natural human-robot interaction styles. Robot Auton Syst 54:127–134. https://doi.org/10.1016/j.robot.2005.09.022Sanghvi J, Castellano G, Leite I et al (2011) Automatic analysis of affective postures and body motion to detect engagement with a game companion. In: Proceedings of the 6th international conference on human–robot interaction—HRI’11. ACM Press, New York, pp 305–311Sanna A, Lamberti F, Paravati G, Manuri F (2013) A Kinect-based natural interface for quadrotor control. Entertain Comput 4:179–186. https://doi.org/10.1016/j.entcom.2013.01.001Sato E, Yamaguchi T, Harashima F (2007) Natural interface using pointing behavior for human–robot gestural interaction. IEEE Trans Ind Electron 54:1105–1112. https://doi.org/10.1109/TIE.2007.892728Schaper M-M, Pares N (2016) Making sense of body and space through full-body interaction design. In: Proceedings of the 15th international conference on interaction design and children—IDC’16. ACM Press, New York, pp 613–618Schaper M-M, Malinverni L, Pares N (2015) Sketching through the body: child-generated gestures in full-body interaction design. In: Proceedings of the 14th international conference on interaction design and children—IDC’15. ACM Press, New York, pp 255–258Seyed T, Burns C, Costa Sousa M et al (2012) Eliciting usable gestures for multi-display environments. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfaces—ITS’12. ACM Press, New York, p 41Shimon SSA, Morrison-Smith S, John N et al (2015) Exploring user-defined back-of-device gestures for mobile devices. In: Proceedings of the 17th international conference on human–computer interaction with mobile devices and services—MobileHCI’15. ACM Press, New York, pp 227–232Sipitakiat A, Nusen N (2012) Robo-blocks: a tangible programming system with debugging for children. In: Proceedings of the 11th international conference on interaction design and children—IDC’12. ACM Press, New York, p 98Soler-Adillon J, Ferrer J, Pares N (2009) A novel approach to interactive playgrounds: the interactive slide project. In: Proceedings of the 8th international conference on interaction design and children—IDC’09. ACM Press, New York, pp 131–139Stiefelhagen R, Fogen C, Gieselmann P et al (2004) Natural human–robot interaction using speech, head pose and gestures. In: 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS) (IEEE Cat. No. 04CH37566). IEEE, New York, pp 2422–2427Subrahmanyam K, Greenfield PM (1994) Effect of video game practice on spatial skills in girls and boys. J Appl Dev Psychol 15:13–32. https://doi.org/10.1016/0193-3973(94)90004-3Sugiyama J, Tsetserukou D, Miura J (2011) NAVIgoid: robot navigation with haptic vision. In: SIGGRAPH Asia 2011 emerging technologies SA’11, vol 15, p 4503. https://doi.org/10.1145/2073370.2073378Takahashi T, Morita M, Tanaka F (2012) Evaluation of a tricycle-style teleoperational interface for children: a comparative experiment with a video game controller. In: 2012 IEEE RO-MAN: the 21st IEEE international symposium on robot and human interactive communication. IEEE, New York, pp 334–338Tanaka F, Takahashi T (2012) A tricycle-style teleoperational interface that remotely controls a robot for classroom children. In: Proceedings of the seventh annual ACM/IEEE international conference on human–robot interaction—HRI’12. ACM Press, New York, pp 255–256Tjaden L, Tong A, Henning P et al (2012) Children’s experiences of dialysis: a systematic review of qualitative studies. Arch Dis Child 97:395–402. https://doi.org/10.1136/archdischild-2011-300639Vatavu R-D (2012) User-defined gestures for free-hand TV control. In: Proceedings of the 10th European conference on interactive TV and video—EuroiTV’12. ACM Press, New York, pp 45–48Vatavu R-D (2017) Smart-Pockets: body-deictic gestures for fast access to personal data during ambient interactions. Int J Hum Comput Stud 103:1–21. https://doi.org/10.1016/j.ijhcs.2017.01.005Vatavu R-D, Wobbrock JO (2015) Formalizing agreement analysis for elicitation studies: new measures, significance test, and toolkit. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems—CHI’15. ACM Press, New York, pp 1325–1334Vatavu R-D, Wobbrock JO (2016) Between-subjects elicitation studies: formalization and tool support. In: Proceedings of the 2016 CHI conference on human factors in computing systems—CHI’16. ACM Press, New York, pp 3390–3402Voyer D, Voyer S, Bryden MP (1995) Magnitude of sex differences in spatial abilities: a meta-analysis and consideration of critical variables. Psychol Bull 117:250–270. https://doi.org/10.1037/0033-2909.117.2.250Wainer J, Robins B, Amirabdollahian F, Dautenhahn K (2014) Using the humanoid robot KASPAR to autonomously play triadic games and facilitate collaborative play among children with autism. IEEE Trans Auton Ment Dev 6:183–199. https://doi.org/10.1109/TAMD.2014.2303116Wang Y, Zhang L (2015) A track-based gesture recognition algorithm for Kinect. Appl Mech Mater 738–7399:334–338. https://doi.org/10.4028/www.scientific.net/AMM.738-739.334

Attracting Human Attention Using Robotic Facial Expressions and Gestures

Robots will soon interact with humans in settings outside of a lab. Since it will be likely that their bodies will not be as developed as their programming, they will not have the complex limbs needed to perform simple tasks. Thus they will need to seek human assistance by asking them for help appropriately. But how will these robots know how to act? This research will focus on the specific nonverbal behaviors a robot could use to attract someone’s attention and convince them to interact with the robot. In particular, it will need the correct facial expressions and gestures to convince people to help them

Use of human gestures for controlling a mobile robot via adaptive CMAC network and fuzzy logic controller

Mobile robots with manipulators have been more and more commonly applied in extreme and hostile environments to assist or even replace human operators for complex tasks. In addition to autonomous abilities, mobile robots need to facilitate the human–robot interaction control mode that enables human users to easily control or collaborate with robots. This paper proposes a system which uses human gestures to control an autonomous mobile robot integrating a manipulator and a video surveillance platform. A human user can control the mobile robot just as one drives an actual vehicle in the vehicle’s driving cab. The proposed system obtains human’s skeleton joints information using a motion sensing input device, which is then recognized and interpreted into a set of control commands. This is implemented, based on the availability of training data set and requirement of in-time performance, by an adaptive cerebellar model articulation controller neural network, a finite state machine, a fuzzy controller and purposely designed gesture recognition and control command generation systems. These algorithms work together implement the steering and velocity control of the mobile robot in real-time. The experimental results demonstrate that the proposed approach is able to conveniently control a mobile robot using virtual driving method, with smooth manoeuvring trajectories in various speeds