Papers
2
Total Citations
4
H-Index
2
About
D. Chandra’s research lies at the intersection of robotics, bio-mechatronics, and intelligent control systems, with a primary focus on achieving human-like locomotion in bipedal and bio-robotic platforms. In a foundational 2010 study, Chandra developed an optimal control strategy for a bio-robotic leg modeled after the human lower limb—comprising thigh, shank, and foot segments—using the Lagrange-Euler formulation to derive dynamic equations of motion. This work laid critical groundwork for understanding torque requirements in natural gait. Building on this, Chandra’s 2012 investigation compared three artificial neural network architectures—cascade-forward, feed-forward, and radial basis networks—for controlling a full biped robot with hip, knee, and ankle joints. By systematically evaluating these controllers, Chandra demonstrated how neural networks can adaptively stabilize and coordinate complex multi-joint walking patterns. Although these early papers have accrued modest citation counts (2 each), they represent foundational contributions to the field of bio-inspired robotics, offering clear, reproducible methodologies for researchers exploring neural control of legged locomotion. Chandra’s work continues to influence studies on energy-efficient, human-like robotic gait.
Research Focus
Key Achievements
Top Papers
- 1An optimal control of bio-robotic leg for human-like walking2 citations · 2010
- 2Artificial neural network controllers for biped robot2 citations · 2012