Robotics: control, sensing, vision, and intelligence
Robotics: control, sensing, vision, and intelligence
An experiment in linguistic synthesis with a fuzzy logic controller
International Journal of Human-Computer Studies - Special issue: 1969-1999, the 30th anniversary
Biped Locomotion
Machines That Walk: The Adaptive Suspension Vehicle
Machines That Walk: The Adaptive Suspension Vehicle
Evolving Fuzzy Logic Controllers for Sony Legged Robots
RoboCup 2001: Robot Soccer World Cup V
Adaptive network based fuzzy control of a dynamic biped walking robot
IJSIS '96 Proceedings of the 1996 IEEE International Joint Symposia on Intelligence and Systems
Trajectory Generation Using GA for an 8 DOF Biped Robot with Deformation at the Sole of the Foot
Journal of Intelligent and Robotic Systems
A New Kind of Hybrid Filter Based on the ICM and the Peak-and-Valley Filter
IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
Soft Computing
Near-optimal gait generations of a two-legged robot on rough terrains using soft computing
Robotics and Computer-Integrated Manufacturing
Ascending and descending stairs for a biped robot
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
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This paper deals with the generation of dynamically balanced gaits of a ditch-crossing biped robot having seven degrees of freedom (DOFs). Three different approaches, namely analytical, neural network (NN)-based and fuzzy logic (FL)-based, have been developed to solve the said problem. The former deals with the analytical modeling of the ditch-crossing gait of a biped robot, whereas the latter two approaches aim to maximize the dynamic balance margin of the robot and minimize the power consumption during locomotion, after satisfying a constraint stating that the changes of joint torques should lie within a pre-specified value to ensure its smooth walking. It is to be noted that the power consumption and dynamic balance of the robot are also dependent on the position of the masses on various links and the trajectory followed by the hip joint. A genetic algorithm (GA) is used to provide training off-line, to the NN-based and FL-based gait planners developed. Once optimized, the planners will be able to generate the optimal gaits on-line. Both the NN-based and FL-based gait planners are able to generate more balanced gaits and that, too, at the cost of lower power consumption compared to those yielded by the analytical approach. The NN-based and FL-based approaches are found to be more adaptive compared to the other approach in generating the gaits of the biped robot.