Comments (3)
rayvburn
commented on July 28, 2024
TODO:
cfg_->static_obj_interaction == INTERACTION_REPULSIVE_EVASIVEsocial_force_model.cpp:281- this should be considered insideworldorhubero_planner(better)
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rayvburn
commented on July 28, 2024
TODO:
* `cfg_->static_obj_interaction == INTERACTION_REPULSIVE_EVASIVE` * `social_force_model.cpp:281` - this should be considered inside `world` or **`hubero_planner`** (better)
World::addObstacle(..., bool force_dynamic_type = false)
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rayvburn
commented on July 28, 2024
- TODO: Dynamic obstacles force calculation needs to be verified. Easiest way is to debug via
static_obj_interactionparam (force all obstacles to be treated as dynamic)
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Related Issues (20)
- adjust `getPoseFromPlan` method of the planner HOT 1
- Goal pose gradually moved away by small distances does not get updated
- consider adding `SlowMovementCostFunction` HOT 5
- Update default parameter values in the `Config` struct according to the `dynamic_reconfigure` setup
- consider adding `ObstacleSeparationCostFunction` HOT 3
- consider assigning negative TTC cost to trajectories that will cause collision in the first prediction step
- do not switch state from `Adjust` to `Init` when the goal is closer than double `xy_tolerance` HOT 2
- `CostParams` struct cleanup
- investigate memory corruption errors HOT 1
- try to improve a robot behaviour when entering narrow passages (e.g., doors)
- investigate source of invalid `relative location` in Trapezoids HOT 2
- unhandled case in `TrapezoidParted`
- consider copying objects of the sparse environment model to avoid using mutexes for the whole planning procedure HOT 3
- parameterize cost functions to evaluate the whole trajectory vs only the first step
- fix `ros::TimeNotInitializedException` in unit tests
- prepare Turtlebot example
- Add a recovery behaviour once the global plan has not been updated for N planning periods HOT 1
- consider extending the `PathCrossingDetector` with the analysis of the global path plan
- consider recalculating `occdist_scale` dynamically to increase the clearance from obstacles when the robot is far from the goal
- decouple prediction and planning
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