Fix indexing for joint parameters in randomize_joint_parameters class

[GiulioRomualdi]

Description

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List any dependencies that are required for this change.

Fixes #4050

Type of change

• Bug fix (non-breaking change which fixes an issue)

Screenshots

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Checklist

• I have read and understood the contribution guidelines
• I have run the pre-commit checks with ./isaaclab.sh --format
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• I have updated the changelog and the corresponding version in the extension's config/extension.toml file
• I have added my name to the CONTRIBUTORS.md or my name already exists there

[greptile-apps]

Greptile Overview

Greptile Summary

Fixed a critical shape mismatch bug in randomize_joint_parameters that caused runtime errors during environment initialization. The issue occurred when indexing joint parameter tensors - the code was incorrectly applying env_ids[:, None] broadcasting in all cases, creating tensors with shape (num_envs, 1, num_joints) instead of the expected (num_envs, num_joints).

Key Changes:

• Introduced env_ids_for_slice variable that conditionally applies [:, None] broadcasting only when both env_ids and joint_ids are tensors
• Applied the fix consistently across all joint parameter writes: friction coefficients (static, dynamic, viscous), armature, and position limits
• The fix aligns with how downstream methods (e.g., write_joint_friction_coefficient_to_sim) expect to receive parameter tensors

Impact:

• Resolves RuntimeError: shape mismatch that prevented startup randomization of actuator parameters
• Maintains correct behavior for all edge cases: when either or both of env_ids/joint_ids are slices vs tensors

Confidence Score: 5/5

• This PR is safe to merge with high confidence
• The fix is minimal, well-targeted, and correctly addresses the root cause. The logic properly handles all edge cases (slice vs tensor combinations), follows the same pattern used in downstream methods, and resolves a critical bug that completely blocked the feature
• No files require special attention

Important Files Changed

File Analysis

Filename	Score	Overview
source/isaaclab/isaaclab/envs/mdp/events.py	5/5	Fixed tensor shape mismatch by conditionally applying broadcasting only when both env_ids and joint_ids are tensors

Sequence Diagram

sequenceDiagram
    participant User as User Code
    participant RJP as randomize_joint_parameters
    participant Helper as _randomize_prop_by_op
    participant Asset as Articulation Asset
    
    User->>RJP: Call with env_ids & joint_ids (tensors)
    
    Note over RJP: Determine env_ids_for_slice<br/>if both are tensors:<br/>env_ids_for_slice = env_ids[:, None]<br/>else: env_ids_for_slice = env_ids
    
    RJP->>Helper: Call _randomize_prop_by_op(data, env_ids, joint_ids)
    Note over Helper: Returns tensor shape (num_envs, num_joints)
    Helper-->>RJP: friction_coeff tensor
    
    RJP->>RJP: Index: friction_coeff[env_ids_for_slice, joint_ids]
    Note over RJP: Result shape: (num_envs, num_joints)<br/>NOT (num_envs, 1, num_joints)
    
    RJP->>Asset: write_joint_friction_coefficient_to_sim<br/>(static_friction_coeff, env_ids, joint_ids)
    Note over Asset: Asset expects shape:<br/>(len(env_ids), len(joint_ids))
    Asset->>Asset: Internally applies env_ids[:, None] for indexing
    Asset-->>RJP: Success

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