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Proprioceptive feedback paradigm for safe and resilient motion control

Mrdjan Jankovic

Abstract

Proprioception is a human sense that provides feedback from muscles and joints about body position and motion. This key capability keeps us upright, moving, and responding quickly to slips or stumbles. In this paper we discuss a proprioception-like feature (machine proprioceptive feedback - MPF) for motion control systems. An unexpected response of one actuator, or one agent in a multi-agent system, is compensated by other actuators/agents through fast feedback loops that react only to the unexpected portion. The paper appropriates the predictor-corrector mechanism of decentralized, multi-agent controllers as "proprioceptive feedback" for centrally controlled ones. It analyzes a nature and degree of impairment that can be managed and offers two options, full- MPF and split-MPF, with different wiring architectures as well as different stability and safety properties. Multi-vehicle interchange lane-swap traffic simulations confirm the analytical results.

Proprioceptive feedback paradigm for safe and resilient motion control

Abstract

Proprioception is a human sense that provides feedback from muscles and joints about body position and motion. This key capability keeps us upright, moving, and responding quickly to slips or stumbles. In this paper we discuss a proprioception-like feature (machine proprioceptive feedback - MPF) for motion control systems. An unexpected response of one actuator, or one agent in a multi-agent system, is compensated by other actuators/agents through fast feedback loops that react only to the unexpected portion. The paper appropriates the predictor-corrector mechanism of decentralized, multi-agent controllers as "proprioceptive feedback" for centrally controlled ones. It analyzes a nature and degree of impairment that can be managed and offers two options, full- MPF and split-MPF, with different wiring architectures as well as different stability and safety properties. Multi-vehicle interchange lane-swap traffic simulations confirm the analytical results.

Paper Structure

This paper contains 14 sections, 23 equations, 8 figures, 3 tables.

Figures (8)

  • Figure 2: a) Proprioceptive feedback structure in human muscles; b) machine proprioceptive loops for a two degree of freedom controller -- e.g., steering ($u_1$) and acceleration ($u_2$) in a vehicle -- considered in this paper.
  • Figure 3: A model of a "difference calculator" that produces an actionable signal from the proprioceptive feedback (based on proskebays).
  • Figure 4: Split-MPF configuration: separate controllers control each actuator while reacting to other actuator's unexpected response.
  • Figure 5: Two still frames taken 5s apart from an interchange traffic video. Blue vehicles go from right to left lane and and red vehicles from left to right. The pale red vehicle has lost propulsive power at -20m marker.
  • Figure 6: Acceleration profiles for all sixteen vehicles of a single run.
  • ...and 3 more figures