Co-Management of Communication and Computational Energy in Wirelessly Connected Mobile Robots

Battery-powered mobile robots that rely on an edge server for perception spend energy in three places at once: the on-board processor, the radio front end and the drivetrain. These budgets are normally optimised separately, which is a mistake, as lowering the processor clock pushes work onto the wireless link, transmitting into a poor channel costs far more than waiting for a better one, and where the robot drives determines what the channel will be. We formulate the co-management of all three as a minimisation of long-run average energy for a fleet sharing an access point and subject to task deadlines, a power budget and a mission-progress constraint that forces every policy under comparison to cover the same ground. The resulting stochastic mixed-integer non-convex program is made tractable by a Lyapunov drift-plus-penalty argument that decomposes it into four per-slot subproblems: a square-root clock rule, a water-filling transmit-power rule with an explicit on/off test, a join-the-shorter-queue offloading split, and a short lookahead over admissible speeds. The policy needs no channel or workload statistics and attains an A per-task deadline mechanism, feasibility floors on the clock and transmit decisions, and closes the gap between queue-stability guarantees and individual task deadlines, which drift arguments alone do not bound. The policy needs no channel or workload statistics and attains an [O(1/V),O(V)] energy–delay tradeoff, stated under precisely qualified assumptions. In a per-task simulation study against six baselines, the policy reduced combined communication and computation power by 25% relative to the strongest deadline-compliant baseline (p<10−4) at equal mission progress, and was the only scheme to hold deadline violations below 0.5% across the full load range, where every baseline exceeded 16% at high load.