Carnegie Mellon Zoë Vehicle Controller Design Design Review December 19, 2003 Michael Wagner 

Carnegie Mellon Aspects of Controller Design Chassis redesign Evaluate Hyperion controller design in terms of: Changing algorithms, exposing variables Ease of use Power consumption of hardware Integrating instrument deployment Reliability for multi-day operation

Carnegie Mellon Chassis Redesign Turn Radius 2 passive steering pivots 2 roll pivots Kinematics similar to Hyperion

Carnegie Mellon How to Control It? Initial tests show that the chassis naturally tends towards an incorrect configuration not…

Carnegie Mellon Controller Performance Robot stopped, axles both angled to the right Front wheel over block Rear wheel over block

Carnegie Mellon Controller Performance Robot stopped Front wheel over block Rear wheel over block

Carnegie Mellon Controller Architecture PI Controller Galil Motion Controller Robot Kinematic Model Vehicle Controller, Pendant dd vdvd  inner,front + +  ticks/s aa + E rad+ – – ++ + aa cc PID  = K p (  d –  a ) + K I  (  d –  a )  outer,front  outer,rear  inner,rear PI Controller + +  ticks/s + E rad + – – + + +

Carnegie Mellon Slip Control Idea is to control slip ratio [Yoshida03] s = r  – v / r  Slip ratio should be small to travel over terrains Slip ratio of 1 means the wheels are just spinning on the soil Must reliably measure both  and v Angular wheel velocity is easy to measure with encoders Rover velocity is trickier without GPS

Carnegie Mellon Instrument Controllers Software blocks to interface with the science “instruments”: SPI cameras Spectrometer Fluorescence camera SPI pan/tilt Underbelly deployment mechanism Each component must: Reliably carry out command Know when failures occur, report this to executive

Carnegie Mellon Instrument Controllers Blocks must be split up to allow complex science operations, for instance: Stop robot Deploy fluorescence imager to (x 0,z 0 ) Take fluorescence image Move robot ahead by y 0 (NOTE: how do we check that this is safe?) Take fluorescence image

Carnegie Mellon Control Hardware Several instrument controllers must interface with motion control hardware 8 axes to control: 4 drive motors (w/o sinusoidal commutation) 2 SPI pan/tilt motors 2 underbelly deployment mechanism (x / z) But also some simpler motions that may not require sophisticated control hardware Plow deployment Calibration target deployment Shroud deployment Filter wheels, dust covers, …

Carnegie Mellon Next Steps Test Hyperion’s motion controller with Zoe amplifiers and drive motors Tune steering controllers for rough terrain Analyze failure modes See if control / power performance is as expected Improve reliability of Vehicle Controller process Handle “odd” motion controller conditions (amps, limit switches, etc.) Instrument more variables for State Observer and Health Monitor Implement chassis self-calibration

Carnegie Mellon Next Steps Prototype instrument controllers: Pan/tilt Underbelly deployment (in conjunction with safe driving) Design “control” for simple actions (shroud, plow, etc.)

Carnegie Mellon That’s it Muchas gracias ¿Preguntas?

Carnegie Mellon Goals of Redesigned Chassis Support science payload under chassis Create overlapping fields of view Support “recover maneuver” to autonomously back out of non-traversable regions Provide maneuverability to approach targets in the morning within panorama from Sol N-1

Carnegie Mellon Double Passive-Steered Chassis Metric Double Passive-Steered Mechanical ComplexityExtra complexity to couple steering motions. Turning RadiusMuch tighter turning radii possible. Controller ModificationsModifications required to vehicle controller. StabilityLess stable in tight turns. Expected MassExtra mass required for steering motion coupler. Expected Power DrawSmaller stresses on frame should reduce power draw. Ease of Science Instrument IntegrationNo fixed rear axle to attach science instruments. Dead Reckoning AccuracyLess wheel slip should provide better information about vehicle state. Symmetry of Fwd and Reverse DrivingMotion should be symmetric Failure ModesHard stops needed to avoid collapse.

Carnegie Mellon Controller Performance Robot stopped Front wheel over block Rear wheel over block