• Intelligent Control
  
  System identification and control of nonlinear systems can be efficiently carried out using intelligent control schemes. In this framework, our research work primarily focus on direct, indirect and model predictive control schemes using T-S fuzzy model, neural and fuzzy-neural networks. These control algorithms are being tested in real-time systems such as 7DOF Power-cube robot manipulator and inverted pendulum

• Visual Servoing
  
  Visual-motor coordination, also referred to as hand-eye coordination, in the context of robotics is the process of using visual information to control a robot manipulator to reach a target point in its workspace. The task requires learning the mapping that exists between camera output and desired end-effector location. Biological organisms have demonstrated their superior adaptive capabilities in motion control over present-day robotic systems. Inspired by this fact, various neural network models based on biological systems have been developed for robot control tasks. We have been working on various self-organizing schemes such as Kohonen SOM, Quantum clustering SOM and parametrized SOM to learn this map using minimum learning example. Simultaneously we are extending these approaches to the redundant manipulator system which involves optimization of multiple objective functions. Current research includes development of redundancy preserving SOM network and adaptive critic based visual servo control

• Neural Networks
  
  Research in this area focuses on efficient training schemes that would provide faster convergence, better generalization and least computational effort. Research work concerning quantum neural networks is also being carried out; some of these works have generated keen interest among peers

• Visual Navigation of a Mobile Robot
  
  Navigation is the process of planning and controlling the movement of a craft or vehicle from one place to another. Navigation in the context of robot includes three basic tasks
  (1) object tracking
  (2) estimation of depth and angle of object from the robot
  (3) obstacle avoidance.
  Various intelligent techniques such as TS fuzzy networks are used to develop higher-level sensory-motor coordination algorithms. Besides novel approaches for formation control and coordination of multi-robot systems are being developed

• Assistive Robotics - Optimal Hand Exoskeleton
  
  An optimal hand exoskeleton device for the impaired hand of the stroke patients is being developed. Each link in the finger is replicated by a four-bar mechanism which takes care of the instantaneously varying joint centres. The developed exoskeleton will generate flexible human like motion based on biological signals derived from the muscle/brain signals that directly reflect the subjects intension. The developed device can be used for the following cases
  (i) To support the fingers of elderly persons who have reduced control over their finger force
  (ii) Active hand prosthetics who have lost their fingers
  (iii) Rehabilitation of patients with finger injury or neuro-muscular diseases

• Laxmidhar Behera and Indrani Kar, Intelligent Systems and Control: Principles and Applications, Oxford University Press, Nov 2009

• Indrani Kar and Laxmidhar Behera,Direct adaptive neural control for affine nonlinear systems, Applied Soft Computing, Vol. 9, pp.756-764, 2009

• K. Srinivas, and Laxmidhar Behera, Swing Up Control Strategies for a Reaction Wheel Pendulum, International Journal of Systems Science, Vol 39, No 12, 1165-1177, 2008

• Prem Kumar P., Indrani Kar and Laxmidhar Behera Variable gain controllers for nonlinear systems using T-S Fuzzy model, IEEE Trans Systems, Man and Cybernetics, Part B,Vol. 36, No. 6, pp1442-1449,2006

• Laxmidhar Behera, Query based model learning and stable tracking of a robot arm using radial basis function network, Computers and Electrical Engineering 29 (2003) 553-573

• Swagat Kumar, Laxmidhar Behera and TM McGinnity, Kinematic control of a redundant manipulator using inverse-forward adaptive scheme with a KSOM based hint generator, Robotics and Autonomous Systems,doi:10.1016/j.robot.2009.12.002, 2009

• Indrani Kar and Laxmidhar Behera, Visual Motor Control of a 7 DOF Robot Manipulator Using a Fuzzy SOM Network, Intelligent Service Robotics, Vol 3, No 1, pp 49-60, 2010

• Swagat Kumar, Prem Kumar, Ashish Dutta and Laxmidhar Behera,Visual Motor Control of a 7DOF Redundant Manipulator using Redundancy Preserving Learning Network, Robotica, doi:10.1017/S026357470999049X, 2009

• Swagat Kumar and Laxmidhar Behera, Visual Motor Control of a 7DOF Robot Manipulator Using Function Decomposition and Sub-clustering in Configuration Space, Neural Processing Letters. Vol. 28, No. 1, pp 17-33, 2008

• Nimit Kumar and Laxmidhar Behera, Visual Motor Coordination Using a Quantum Clustering Based Neural Control Scheme, Neural Processing Letters,Volume 20: 11-22, 2004

• Laxmidhar Behera, Swagat Kumar and Awhan Patnaik, On adaptive learning rate that guarantees convergence in feed-forward networks, (To be published) IEEE Trans Neural Networks, Vol. 17, No. 5 September 2006

• Laxmidhar Behera, Indrani Kar and Avshalom C. Elitzur, Recurrent Quantum Neural Network Model to Describe Eye Tracking of Moving Target, Foundations of Physics Letters, Vol. 18, No. 4, 357-370, 2005

• Laxmidhar Behera and Bharat Sundaram, Stochastic filtering and and Speech Enhancement using a Recurrent Quantum Neural Network, Proceedings Int. Conf. Int. Sensors and Inf. Processing, ICISIP-2004, Chennai, 165-170;Received Best Paper Award

• Laxmidhar Behera, Indrani Kar and A.C. Elitzur, Chapter 9: Recurrent Quantum Neural Network and Its Applications, in The Emerging Physics of Consciousness, Jack Tuszynski (Ed), Springer Verlag, 2005

• Anjan Kumar Ray, Patrick Benavidez, Laxmidhar Behera and Mo Jamshidi, Decentralized Motion Coordination for a Formation of Rovers, IEEE Systems Journal, Vol 3, No. 3, pp369-381, Sept 2009

• Anjan K Ray, Laxmidhar Behera and Mo Jamshidi, Sonar Based Rover Navigation for a Single or Multiple Platforms: Forward Safe Path and Target Switching Approach, IEEE Systems Journal, Vol 2, No. 2, pp. 258-272, 2008

• Meenakshi Gupta, T Naveen Kumar, Laxmidher Behera, K S Venkatesh and Ashish Dutta, Environment Modelling in Mobile Robotics through Takagi-Sugeno Fuzzy Model, Irish Signal and Systems Conference (ISSC), 2009, Dublin

• DST Sponsored Project on Intelligent Visual Control of Redundant Manipulator Systems for Grasping 3-D Objects, Rs 32 Lakhs, 2000
  Status: Ongoing

• DRDO Sponsored Project on Visual Motor Control of a Seven Degrees of Freedom Robot Manipulator, Rs. 50 lakhs at IIT Kanpu
  Status: Ongoing

• UKIERI Standard Research Award of GBP 144,000.00 on ‘Innovations in Intelligent Assistive Robotics’
  Status: Ongoing

• Quantum Neural Network Models - Applications of Quantum Learning to Health Care System and Visual Tracking System, Funded by Ministry of Human Resource and Development, India from 2005-2008, Rs 20.00 lakhs
  Status: Completed

• Intelligent Control Schemes and Application to Dynamic and Visual Control of Redundant Manipulator Systems, Funded by Department of Science and Technology, India from 2006-2008, Rs 20.00 lakhs
  Status: Completed

• Infrastructure development in Intelligent Sensors and Control, FIST grant from Department of Science and Technology, India, 2005-2007, Rs 65.00 lakhs
  Status: Completed

• MHRD Sponsored project, Adaptive nonlinear control - A foundational framework using classical and quantum algorithms, Rupees 6.00 lakhs, IIT, Kanpur
  Status: Completed

• Awhan Patnaik
• Prem Kumar P
• Felix Orlando
• Meenakshi Gupta
• Vipul Arora

• Himansu Singh
• Benami Singh
• Chandrajit Choudhury

• 7DOF Power-cube robot manipulator and inverted pendulum

• Visual Servoing

• Patrolbot

• Assistive Robotics - Optimal Hand Exoskeleton

Dr. Laxmidhar Behera

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Phone: 91 512 259 7198
Location: WL213