Towards Proactive Replanning for Multi-Robot Teams Brennan Sellner and Reid Simmons 5th International Workshop on Planning and Scheduling for Space October 23, 2006 Trestle Project Robotics Institute Carnegie Mellon University

IWPSS Brennan Slide 2 Motivation Human workers: Predict likely outcomes Move between teams mid-task Can multi-robot teams do the same?

IWPSS Brennan Slide 3 What is Proactive Replanning? Predict problems and opportunities Replan before they manifest

IWPSS Brennan Slide 4 Idea Iterative repair planner Add Proactive Replanning Duration Prediction Live Task Modification Replan and modify active teams to: Forestall problems Grasp opportunities

IWPSS Brennan Slide 5 Results Preview Stochastic domain Metric is schedule makespan Makespan reductions of 11-32%

IWPSS Brennan Slide 6 Approach Overview Domain Architecture Duration Prediction Live Task Modification

IWPSS Brennan Slide 7 Domain Multi-agent, multi-team assembly Goal: Minimize schedule length

IWPSS Brennan Slide 8 Scenario

IWPSS Brennan Slide 9 Architecture Planner (ASPEN): Centralized Repairs & optimizes schedule Dispatches tasks Duration Prediction & Live Task Modification Executive: Manages execution of tasks Monitors resource usage Transmits state to planner Behavioral: Interfaces with hardware Transmits state to executive Behavioral and hardware both simulated

IWPSS Brennan Slide 10 Planner ASPEN: Iterative repair and optimization Duration Prediction within constraint network Live Task Modification during repair and optimization

IWPSS Brennan Slide 11 Planner: Conflict Resolution

IWPSS Brennan Slide 12 Planner: Optimization Metric: schedule length Use idle agents to: Start tasks on the “critical path” Speed up executing tasks on the critical path

IWPSS Brennan Slide 13 Duration Prediction: Why?

IWPSS Brennan Slide 14 Duration Prediction: How? Predict remaining duration at each timestep Replan in response Challenge: Accurate predictions within resource bounds Current approach: Offline simulation + lookup table

IWPSS Brennan Slide 15 Live Task Modification: Why?

IWPSS Brennan Slide 16 Live Task Modification: How? As part of schedule repair or optimization Heuristically select a new team Subject to constraints Currently assume instant transfers

IWPSS Brennan Slide 17 Live Task Modification: How? Challenge: search large space of teams and agents

IWPSS Brennan Slide 18 Experimental Results Scenario Conditions Data

IWPSS Brennan Slide 19 Experimental Scenario

IWPSS Brennan Slide 20 Experimental Approach 50 simulated assemblies per condition 4 conditions

IWPSS Brennan Slide 21 Baseline Condition ASPEN No Proactive Replanning Each time step: Right-shift Left-shift Optimize Repair

IWPSS Brennan Slide 22 Experimental Conditions Baseline, plus: Prediction, or: Live Modification, or: Combined

IWPSS Brennan Slide 23 Summary of Results

IWPSS Brennan Slide 24 Results Details 50 runs per condition mean (std dev) Baseline (ASPEN) PredictionModificationCombination Schedule length (s) (343.58) (273.32) (123.55) (141.53) Reduction in length ---- (----)10.8%30.3%31.8% Repair episodes (36.60) (23.06) (8.00) (23.86) Useful team modifications (6.15) (5.46) (6.19) (7.58)

IWPSS Brennan Slide 25 Future Work Function approximation and Duration Prediction Durative agent transfers Risk management

IWPSS Brennan Slide 26 Summary Initial implementation of Proactive Replanning Results are promising: Makespan reductions of up to 32% Further work is underway

IWPSS Brennan Slide 27 Thanks! The executive's first name was Tanner, A shy, but proactive, replanner Who solved every trouble With a change, on the double, Which finished the job in fine manner.