docs: add production-style Jetbot Guardrail example#3
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A counterpart to the minimal mobile_base_guardrail.py: a tensor-in/tensor-out JetbotGuardrail wrapper showing the new dict-based Guardrail API on a differential-drive base. Obs (planar pose) and action ([v, omega]) are separate spaces — the boundary callback declares base_pose/action/solvers by name and the runtime injects them, so there is no 5-D vector to assemble. Unsafe commands are QP-corrected in place (osqp), falling back to a full stop (safe_action=[0, 0]) when no QP solver is available. The wrapper keeps only the high-information surface (filter, command_to_wheels, last_results, close) and drops the previous stat-theater (last_decision/last_delta/step_count/ intervention_rate), the unused device arg, and the bundled-path resolver. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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A counterpart to the minimal mobile_base_guardrail.py: a tensor-in/tensor-out JetbotGuardrail wrapper showing the new dict-based Guardrail API on a differential-drive base. Obs (planar pose) and action ([v, omega]) are separate spaces — the boundary callback declares base_pose/action/solvers by name and the runtime injects them, so there is no 5-D vector to assemble.
Unsafe commands are QP-corrected in place (osqp), falling back to a full stop (safe_action=[0, 0]) when no QP solver is available. The wrapper keeps only the high-information surface (filter, command_to_wheels, last_results, close) and drops the previous stat-theater (last_decision/last_delta/step_count/ intervention_rate), the unused device arg, and the bundled-path resolver.
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