Mobile Intelligent Autonomous Systems

Jitendra Raol, Ajith Gopal
2010 Defence Science Journal  
Mobile intelligent autonomous systems (MIAS) is a fast emerging research area. Although it can be regarded as a general R&D area, it is mainly directed towards robotics. Several important subtopics within MIAS research are: (i) perception and reasoning, (ii) mobility and navigation, (iii) haptics and teleoperation, (iv) image fusion/computer vision, (v) modelling of manipulators, (vi) hardware/software architectures for planning and behaviour learning leading to robotic architecture, (vii)
more » ... le-robot path and motion planning/control, (viii) human-machine interfaces for interaction between humans and robots, and (ix) application of artificial neural networks (ANNs), fuzzy logic/systems (FLS), probabilistic/approximate reasoning (PAR), Bayesian networks (BN) and genetic algorithms (GA) to the above-mentioned problems. Also, multi-sensor data fusion (MSDF) plays very crucial role at many levels of the data fusion process: (i) kinematic fusion (position/bearing tracking), (ii) image fusion (for scene recognition), (iii) information fusion (for building world models), and (iv) decision fusion (for tracking, control actions). The MIAS as a technology is useful for automation of complex tasks, surveillance in a hazardous and hostile environment, human-assistance in very difficult manual works, medical robotics, hospital systems, autodiagnostic systems, and many other related civil and military systems. Also, other important research areas for MIAS comprise sensor/actuator modelling, failure management/ reconfiguration, scene understanding, knowledge representation, learning and decision-making. Examples of dynamic systems considered within the MIAS would be: autonomous systems (unmanned ground vehicles, unmanned aerial vehicles, micro/mini air vehicles, and autonomous underwater vehicles), mobile/fixed robotic systems, dexterous manipulator robots, mining robots, surveillance systems, and networked/multi-robot systems, to name a few.
doi:10.14429/dsj.60.92 fatcat:cl2l3l7hcnby3omkyliw2hvbom