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Project # 20
Energy-Efficient Path Planning for Autonomous Robots Using Lagrangian Mechanics
| Team Lead: | Nafisa Nawrin Labonno |
| Other Team Members: | |
| Faculty Advisor(s): | N/A |
| Department: | CSE |
| Project Type: | Other Undergraduate |
| Title: | Energy-Efficient Path Planning for Autonomous Robots Using Lagrangian Mechanics |
| Abstract: | Autonomous mobile robots for garbage collection and disaster relief face critical challenges: limited battery life, dynamic path planning in unstructured environments, and energy-inefficient navigation. Current path planning algorithms (A*, RRT) rely on geometric heuristics that ignore physical dynamics, resulting in suboptimal energy consumption which is a major constraint when operational time directly impacts mission success. This energy inefficiency compounds in real-world scenarios where robots must navigate debris, handle uncertain terrain, and operate autonomously for extended periods. This independent undergraduate project addresses energy optimization through physics-informed trajectory planning based on Lagrangian mechanics. The system accounts for mass, friction, actuator limits, and energy constraints through numerical optimization methods including shooting and collocation approaches. Implementation focuses on simulation-based validation with potential hardware integration if time permits. The research quantifies trade-offs between optimization objectives (energy minimization, time minimization, trajectory smoothness) through computational experiments. Expected contributions include: 1. Open-source trajectory optimization library implemented from first principles in Python 2. Systematic comparison of planning algorithms under varying constraints 3. Demonstrated energy efficiency improvements over baseline methods. Hardware validation, if achieved, will compare theoretical predictions against measured performance. This work aims to bridge classical mechanics with computational robotics, providing foundational tools applicable to energy-constrained autonomous systems in disaster relief and environmental applications. Keywords: Physics-informed planning, shooting method, collocation, dynamic constraints, computational robotics, autonomous navigation |
| Poster: | View Poster #20 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |