A Movement Control System Based on Qualitative Reasoning
We present \(QR_M\), a movement control system based on Qualitative Reasoning. The representation of relative movement of an object with respect to another is done by using different components given by qualitative values, such as velocity, orientation, latitude, longitude, etc. These qualitative values are obtained from quantitative data by means of a nonlinear system with hysteresis. We also use composition tables for new data inferring and a table-based control system. The system is implemented in Robotic Operating System ROS and tested with computer simulator STAGE. We show how \(QR_M\) works in real applications on the basis of two experiments.
KeywordsQualitative reasoning Qualitative movement Movement Control Collision avoidance
The work presented in this paper is partially supported by the Polish National Science Centre grant 2011/02/A/HS1/00395 and by the Spanish Project TIN12-39353-C04-01.
- 1.Andrea C, Boris G, Fabien S, François C (2013) Avoiding moving obstacles during visual navigation. In: 2013 IEEE international conference on robotics and automation (ICRA), pp 3069–3074. IEEEGoogle Scholar
- 2.Cohn AG, Renz J (2008) Qualitative spatial representation and reasoning. Handb Knowl Represent 3:551–596Google Scholar
- 4.Escrig MT, Toledo F (2002) Qualitative velocity. In: Topics in artificial intelligence, pp 29–39. SpringerGoogle Scholar
- 5.Forbus KD (2008) Qualitative modeling. Handb Knowl Represent 3:361–393Google Scholar
- 6.Frank AU (1992) Qualitative spatial reasoning about distances and directions in geographic space. J Vis Lang Comput 3(4):343–371. ElsevierGoogle Scholar
- 7.Gedig M, Stiemer S (2003) Qualitative and semi-quantitative reasoning techniques for engineering projects at conceptual stage. Electron J Struct Eng 3:67–88Google Scholar
- 8.Gerkey B, Vaughan RT, Howard A (2003) The player/stage project: tools for multi-robot and distributed sensor systems. In: Proceedings of the 11th international conference on advanced robotics, vol 1, pp 317–323Google Scholar
- 9.Khalil HK, Grizzle J (2002) Nonlinear systems, volume 3. Prentice Hall Upper Saddle RiverGoogle Scholar
- 11.Liu W, Li S, Renz J (2009) Combining RCC-8 with qualitative direction calculi: algorithms and complexity. In; IJCAI, pp 854–859Google Scholar
- 13.Quigley M, Conley K, Gerkey B, Faust J, Foote T, Leibs J, Wheeler R, Ng AY (2009) ROS: an open-source robot operating system. In: ICRA workshop on open source software, vol 3, p 5Google Scholar
- 14.Van de Weghe N, Kuijpers B, Bogaert P, De Maeyer P (2005) A qualitative trajectory calculus and the composition of its relations. In: GeoSpatial Semantics, pp 60–76. SpringerGoogle Scholar
- 15.Zvi S, Frederic L, Sepanta S (2001) Motion planning in dynamic environments: Obstacles moving along arbitrary trajectories. In: 2001 IEEE international conference on robotics and automation (ICRA), pp 3716–3721. IEEEGoogle Scholar