🧪 Tests to Ensure Reliable Motion Planning

To deliver on our promise of plug-and-play motion planning for common use cases, we need a robust testing framework. This will empower us to consistently validate our solutions and easily benchmark different planner implementations (even those still under development).

**Key Test Suite Requirements**
- 🗺️ **Diverse and Representative:** Cover a range of real-world challenges inspired by the use cases at our lab.
- 🎯 **Targeted:** Isolate specific aspects and highlight planner strengths and weaknesses.
- 💡 **Easy to Grasp:** Named, simple, and clearly defined scenarios.
- 📈 **Gradual Difficulty:** Systematically increasing scenario difficulty pinpoints problems
- 🧐 **Catch User Error:** Discover problems in requested planning queries

To ensure systematic testing, let's organize our test cases in tables like this:

**Joint goals** 🦾
Check whether planning to goal joint configurations works. This can help isolate problems because inverse kinematics is not necessary for this.
| Name | Purpose |
|---|---|
| `01_no_joint_movement` | 🥱 Plan to the same joints as the start and goal |
| `02_single_joint_movement` | ➡️ Plan to close goal joints where only one joint is rotated |
| `03_linear_joint_movement` | 📏 Plan to far joints, but are collision-free when linearly interpolating |
| `04_self_collision_joint_movement` | 💥 Plan to joints that would lead to a self-collision when linearly interpolating |
| `05_env_collision_joint_movement` | 🚫 Plan to joints that would lead to an environment collision |

**User error handling** 🧐
Check whether the planner correctly detects invalid user requests and terminates for infeasible plans.
| Name | Problem |
|---|---|
| `01_start_joints_invalid` | ⚠️ Attempt to plan from invalid start joints |
| `02_goal_joints_invalid` | ⚠️ Attempt to plan to invalid goal joints |