Here are 100 chapter titles covering motion planning algorithms in robotics, progressing from fundamental concepts to advanced techniques:
I. Foundations of Motion Planning (20 Chapters)
- Introduction to Motion Planning in Robotics
- Key Concepts: Configuration Space, Workspace, Obstacles
- Types of Motion Planning Problems: Path Planning, Trajectory Planning
- Performance Metrics for Motion Planning Algorithms
- Configuration Space Representation: Joint Space vs. Cartesian Space
- Obstacle Representation: Polygons, Polyhedra, Voxels
- Discretization of Configuration Space: Grid-Based Approaches
- Graph Search Algorithms: Breadth-First Search, Depth-First Search
- Dijkstra's Algorithm and its Applications in Path Planning
- A* Search Algorithm: Heuristics and Optimality
- Introduction to Sampling-Based Planning
- Random Sampling and Configuration Space Exploration
- Probabilistic Roadmaps (PRMs): Construction and Querying
- Rapidly-exploring Random Trees (RRTs): Growth and Connection
- Basic Motion Planning Algorithms for Mobile Robots
- Motion Planning for Manipulators: Joint Space vs. Task Space
- Introduction to Kinematics and Inverse Kinematics
- Forward and Inverse Kinematics in Motion Planning
- Basic Trajectory Generation Techniques: Linear and Polynomial Interpolation
- Introduction to Robot Control and Motion Execution
II. Intermediate Motion Planning Techniques (30 Chapters)
- Advanced Graph Search Algorithms: Weighted A*, Jump Point Search
- Hierarchical Path Planning: Multi-Resolution Grids, Quadtrees, Octrees
- Multi-Goal Path Planning: Finding Optimal Paths to Multiple Destinations
- Motion Planning with Kinematic Constraints: Nonholonomic Systems
- Planning for Car-like Robots: Reeds-Shepp and Dubins Curves
- Sampling-Based Planning for High-Dimensional Configuration Spaces
- Advanced PRM Techniques: Visibility-Based PRMs, Gaussian Sampling
- Advanced RRT Techniques: RRT*, Informed RRT*
- Path Smoothing and Optimization: Splines, Gradient Descent
- Trajectory Optimization: Time-Optimal, Energy-Optimal, Jerk-Limited
- Introduction to Potential Fields for Motion Planning
- Artificial Potential Functions and their Limitations
- Navigation Functions and Global Planning
- Motion Planning in Dynamic Environments: Time-Varying Obstacles
- Velocity Obstacles and Collision Avoidance
- Predictive Collision Avoidance
- Multi-Robot Path Planning: Coordination and Conflict Resolution
- Decentralized Multi-Robot Planning
- Task Allocation and Path Planning for Multi-Agent Systems
- Motion Planning under Uncertainty: Probabilistic Planning
- Belief Space Planning
- Partially Observable Markov Decision Processes (POMDPs) for Robot Motion
- Introduction to Machine Learning for Motion Planning
- Learning-Based Path Planning
- Reinforcement Learning for Robot Navigation
- Combining Sampling-Based Planning with Machine Learning
- Motion Planning in Cluttered Environments
- Planning for Manipulation Tasks: Grasping and Object Manipulation
- Constraint-Based Motion Planning
- Case Studies: Applications of Motion Planning Algorithms
III. Advanced Motion Planning and Specialized Topics (50 Chapters)
- Advanced Trajectory Optimization Techniques: Direct and Indirect Methods
- Optimal Control for Robot Motion Planning
- Nonlinear Programming for Trajectory Optimization
- Stochastic Motion Planning: Markov Decision Processes (MDPs)
- Robust Motion Planning: Dealing with Uncertainty and Noise
- Motion Planning with Temporal Constraints: Time Windows and Sequencing
- Planning for Human-Robot Collaboration: Shared Workspace Planning
- Motion Planning for Flexible Manipulators
- Planning for Underactuated Robots
- Non-Smooth Optimization for Motion Planning
- Geometric Motion Planning: Cell Decomposition, Visibility Graphs
- Motion Planning in Continuous Configuration Spaces
- Planning with Complex Kinematic Constraints
- Motion Planning for Aerial Robots and Drones
- Motion Planning for Underwater Robots
- Motion Planning for Space Robots
- Motion Planning for Medical Robots
- Motion Planning for Industrial Robots
- Motion Planning for Agricultural Robots
- Motion Planning for Social Robots
- Motion Planning for Humanoid Robots
- Motion Planning for Soft Robots
- Motion Planning for Micro/Nano Robots
- Motion Planning for Swarms of Robots
- Motion Planning in Virtual Environments
- Motion Planning for Augmented Reality Applications
- Motion Planning for Virtual Reality Applications
- Real-time Motion Planning: Fast Replanning and Adaptation
- Hardware Acceleration for Motion Planning Algorithms (GPUs, FPGAs)
- Parallel Computing for Motion Planning
- Distributed Motion Planning: Cloud Robotics
- Motion Planning Libraries and Software Tools (e.g., OMPL, MoveIt!)
- Benchmarking and Evaluating Motion Planning Algorithms
- Performance Analysis and Tuning of Motion Planning Systems
- Debugging and Troubleshooting Motion Planning Problems
- Software Engineering for Motion Planning
- Version Control for Motion Planning Projects
- Collaborative Development of Motion Planning Systems
- Open Source Motion Planning Projects and Contributions
- Motion Planning Education and Training
- Motion Planning Research and Development
- Future Trends in Motion Planning
- Emerging Technologies in Motion Planning
- Ethical Considerations in Motion Planning
- Building a Complete Motion Planning System
- Integrating Motion Planning with Robot Control
- Deploying Motion Planning Algorithms to Real-World Robots
- Maintaining and Upgrading Motion Planning Systems
- Resources and Communities for Motion Planning
- Glossary of Motion Planning Terms