Rekha Raja

IIT Kanpur, ME, Graduate Student

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My name is Rekha Raja and I am a results-oriented and motivated research scientist with using my rich education and experience in computer science, algorithms and robotics to help lead new discoveries. With a PhD in Robotics in Mechanical engineering, I currently work on building new technology to automate industry.I have extensive industry and research experience. I have led and completed several robotics research projects, utilizing a vast knowledge of theoretical and practical skills. From this work, I have published a total of 9 international journal manuscripts and 16 international conference manuscripts, nineteenth as first author, and writing one book chapter, while teaching various courses on robotics, motion planning, MATLAB programming. Additionally, I have collaborated to provide lead on amazon picking challenge project, where the industrial robot is to use to automate the warehouse logistics (pick and place objects from shelves)

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Path planning in dynamic environment for a rover using A∗ and potential field method

This paper proposes a path planning method for a wheeled mobile robot operating in rough terrain ... more This paper proposes a path planning method for a wheeled mobile robot operating in rough terrain dynamic environments using a combination of A∗ search algorithm and potential field method. In this method, the mobile robot uses the structured light system to extract real terrain data as a discrete points to generate a b-spline surface. The terrain is classified based on the slope and elevation using a fuzzy logic controller and a user defined cost function is generated. A combination of A∗ and potential field method has been introduced to find the path from the start location to goal location according to the cost function. The A∗ algorithm determines the path that globally optimizes terrain roughness, curvature and length of the path, and the potential field method has been used as a local planner which performs an on-line planning to avoid the newly detected obstacles by the sensory information. The developed potential function is found to be able to avoid local minima in the work space. The results shows the effectiveness of the proposed algorithm.

New potential field method for rough terrain path planning using genetic algorithm for a 6-wheel rover

Robotics and Autonomous Systems, Oct 1, 2015

h i g h l i g h t s • Proposed a new potential field method for rough terrain path planning for a... more h i g h l i g h t s • Proposed a new potential field method for rough terrain path planning for a rover. • A gradient function is introduced in the conventional potential field method. • The gradient function depends on the roll, pitch and yaw angles of the rover. • Weights of potential field function are optimized by using GA. • Results prove that the new method is superior to conventional potential field method.

Rekha Raja

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