Persistent Profile-Guided Reset-Free Recovery Improves Final Gait Selection after Irreversible Leg Damage

Problem and Evaluation

Figure 1 shows the structural conditions. We simulate a hexapod with two actuated joints per leg in MuJoCo, using a 5-ms time step [ 16 ] . Its gait lifts, advances, and lowers each foot before stance. Damage is applied at a prescribed time without resetting pose, velocity, or contacts. Amputation detaches a whole leg and disables its two actuators. Fracture detaches the distal segment and disables one actuator.

Joint lock fixes both joints at their damage-time positions and disables their actuators. Detached segments remain as dynamic debris.

Profile-Guided Recovery

Figure 2 presents the method in execution order. Panel A describes the offline stage. Each candidate gait is executed repeatedly to form a long-horizon profile, and five GP models per target predict eight outcomes and their uncertainty for candidate gaits. Panel B describes online adaptation after damage.

The policy selects a candidate conservatively, executes a 0.75-s probe, extends viable probes by another 0.75 s, uses the observation to correct its predictions, and runs the current incumbent for 0.75 s as a bridge.

Experimental Protocol

The holdout crosses three damage types, previously unused legs 3–5, friction $\{0.865,1.135\}$, onset $\{1.73,2.37\}$ s, and three candidate seeds. This gives 36 physical conditions and 108 condition–seed tasks. The algorithm, surrogate, metrics, and evaluation procedure were fixed before opening this set. The reported holdout is now consumed and cannot serve as fresh validation after further tuning.

The three adaptive methods share the candidate pool and maximum trial budget.

Results

Across the 108 tasks, PGRR improves SRQ by 0.044 and final quality by 0.106 relative to the IT&E-inspired GP; the low-quality failure rate decreases by 0.278. All three paired intervals exclude zero (Table I ). Final quality improves within amputation, fracture, and joint lock, with joint lock showing the largest paired gain.

Figure 3 shows that PGRR also has higher mean SRQ than the GP comparator in every damage class, although the amputation- and fracture-specific SRQ intervals include zero (Table I ).

Sources and Demonstrations

Figures are reproduced from Kim See the full paper for experimental details and the project page, when the paper links one, for demonstrations and videos.