LiDAR based navigation reward advice needed

I’m training a simple 4-wheel rear drive robot in Isaac Lab. Its task is to navigate to a random target in a 36 m × 36 m arena with obstacles in it

Current reward is

• Goal reached: +120 when inside 1 m goal radius, then episode ends
• Progress: (previous_goal_distance - current_goal_distance) × 4.2
• Heading improvement: improvement in goal-facing alignment × 2.3
• Collision penalty: -0.7 per collision step, but collision does not terminate the episode
• Front obstacle penalty: up to -0.18 when moving forward with an obstacle within 3 m in the front 160-degree LiDAR sector
• Time penalty: -0.01 per step

The problem is even when it hits a wall, it often keeps pushing forward instead of backing up, turning away, or escaping. It may rotate slightly, but then re-aligns to the goal and drives into the wall again.

I tried lowering the progress and heading rewards, but that mostly reduced the goal success rate. Collision time didn’t improve much.

What does a typical reward setup look like for LiDAR based navigation tasks? Am I missing a common recovery or obstacle-avoidance reward?