Strategic Objectives
• Master the foundations of Configuration Space for complex articulated systems.
• Implement real-time obstacle avoidance algorithms for unpredictable environments.
• Bridge the gap between pure geometry and smooth trajectory generation.
• Optimize kinematic chains for maximum efficiency and collision-free movement.
The Core Challenge
Static path planning fails in a world that never stops moving, leaving robots rigid and reactive.
01
The Kinematic Foundation
02
Articulated Systems
03
Mapping the Configuration Space
04
Degrees of Freedom
05
Forward Kinematics
06
Inverse Kinematics
07
The Jacobian Matrix
08
Obstacle Geometry
09
Collision Detection Algorithms
10
Motion Planning Algorithms
11
Sampling-Based Planning
12
Rapidly-exploring Random Trees
13
Potential Fields
14
Trajectory Generation
15
Smoothing and Interpolation
16
Dynamic Environments
17
Velocity Obstacles
18
Holonomic vs. Non-holonomic Constraints
19
Optimization in Planning
20
Real-Time Constraints
21