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Engineering Solutions to Build an Inexpensive Humanoid Robot Based on a Distributed Control Architecture Vítor M. F. Santos1 Filipe M. T. Silva2 1 Department of Mechanical Engineering 2 Department of Electronics and Telecommunications University of Aveiro, PORTUGAL
Overview • Introduction • Initial considerations • Mechanical conception • Actuators, power and batteries • Servomotor issues • Sensorial issues and force sensors • The control architecture • Some preliminary results • Conclusions and open issues
Project framework • Motivation • Develop a humanoid platform for research on control, navigation and perception. • Offer opportunities for under & pos-graduate students to apply engineering methods and techniques • The utopia of Man to develop an artificial being with some of its own capabilities… • Why not a commercial platform? • Versatile platforms imply prohibitive costs! • Reduces the involvement at lowest levels of machine design • Current status • So far, it is only a development engineering approach • The platform prototype already performs some motion • Early studies on control just began
Kawada HRP1S Fujitsu Sumo Bot Sony QRIO ZMP Nuvo Honda Asimo To build or to buy? • Several commercial platforms already exist: • Only a few offer great versatility, DOFs, possibilities of control, … • Good platforms (e.g., Fujitsu) have high costs (tens of thousands of Euros); others are not even for sale • Commercial platforms favour mainly high level software development • Developing a platform from scratch allows using hardware more oriented to the desired approach: • Distributed control, special sensors, alternative central units … • Developing a platform from scratch takes longer, but hopefully can be done at lower costs…
Initial Considerations • Main Objectives • Build a low-cost humanoid robot using off-the-shelf technologies, but still aiming at a fully autonomous platform • Have a working prototype capable of participating in the RoboCup humanoid league (Germany2006) • Design Concerns • Consider a distributed control architecture due to the expected complexity of the final system • Assume modularity at several levels to ease development and scalability • Provide rich sensorial capabilities • Initial design considerations: • Robot dimensions • Mobility skills • Level of autonomy
The needed DOFs • 6 DOFs per leg • Universal joint at the foot (2 DOFs) • Simple joint on the knee (1 DOF) • Spherical joint on the hip (3 DOFs) • Total DOFs for the Legs = 2 x 6 = 12 • Trunk with 2 DOFs • To envisage better balance control • 3 DOFs per arm without hand and wrists • Universal joint on the shoulder (2 DOFs) • Simple joint on the elbow (1 DOF) • Total DOFs for the arms = 2 x 3 =6 • Neck/head accounts for 2 DOFs • To support a camera for vision perception • Total proposed: 22 DOFs
Kinematics simulations • Four Denavit-Hartenberg open kinematics chains: • One leg on the floor up to the opposite foot not on the ground • Starting on the hip, a 2nd chain goes up to the neck. • A 3rd and 4th chain for left and right arms. • Allows the analysis of: • Static torques • Path of CoM and its projection on the ground • Opens the way to simulate: • Dynamics in higher speeds • ZMP paths • Inputs for the model in Matlab: • Links’ DH parameters • Links’ masses • Links’ centers of mass • Path planning at joint level
Mechanical conception Final platfrom 3D model with 600+ components and 22 DOFs Upper hip Head base Lower hip Neck Upper leg Shoulder Trunk Lower leg Arm Trunk joints Ankle Forearm Hip Foot
Summary of mechanical properties • Complete humanoid model • 22 degrees of freedom • Weight - 5 kg • Height - 60 cm • Max width - 25 cm • Foot print - 20 8 (cm2) • Materials used for the body and accessory parts • Aluminium (2.7 g/cm3) • Bronze (8.9 g/cm3) • Steel (7.8 g/cm3) • Nylon (1.4 g/cm3)
Actuators • Static (and some simplified dynamic) simulations were carried out to estimate motor torques in a simulated step • Best low cost actuators in the market are Futaba RF servos or similar (HITEC,…). • Available models best suited for our application are: • Additional mechanical issues for motors • Use gear ratios up to 1:2.5 to rise torques • Use tooth belt systems for easier tuning • Use ball bearings and copper sleeves to reduce friction
Power requirements and batteries • Motors • Max current: 1.2 – 1.5 A per motor (big size model) • Electronics and control • Estimated to less than 200 mA per board with a total of ca. 1.5 A. • Voltage Levels • 5 V for logic; 6.5 V for motors • Two ion-lithium batteries were installed (from Maxx Prod.) • 7.2 V/9600 mAh per pack • Maximal sustained current of 19A • Each pack weights circa 176g • Confined to a box of 373765 (mm3)
Servomotor velocity “control” • Servomotors have an internal controller based on position • User cannot directly control velocity! • Either replace motor own control electronics or do some software tricks • Example: Two similar motors with different velocities • Dynamic PWM generation • Stepped target points • Without load, open-loop and feedback based actuation give similar results…
First results with one leg in motion • Simple open loop actuation of the leg joints • PWMs generated by dedicated boards (shown further on)
Envisaged sensorial capabilities Vision unit (on the head) Gyroscopes for angular velocity GYROSTAR ENJ03JA from MURATA Accelerometers for accelerations and inclinations Potentiometer for position feedback (HITEC Motor) ADXL202E from ANALOG DEVICE Motor electric current Serial power resistor Sensitive feet Strain gauges on a slightly compliant material
The sensitive foot • A device was custom-made using strain gauges properly calibrated and electrically conditioned • Four strain gauges arranged near the four corners of the foot
Force sensors and motor connection Servomotor PIC local board + Electric conditioning Foot sensor Servomotor reacts to differences on sensors located on the edges of the foot
Main Control RS232 Master CAN BUS Slaves 3 3 1 2 2 2 2 1 1 1 3 3 2 2 1 1 3 3 2 2 1 1 Control system architecture • Distributed control system • A network of controllers connected by a CAN bus • A master/multi-slave arrangement • Each slave controller is made of a PIC device with I/O interfacing. • Asynchronous communications • Between master and slaves: CAN bus at 1 Mbit/s • Between master and high level controller (currently serial RS232 at 38400 baud)
Functions of the control level units • Main control unit • Global motion directives; high level planning. • Vision processing • Interface with possible remote hosts • Master CAN controller • Receives orders to dispatch to the slaves • Queries continuously the slaves and keeps the sensorial status of the robot • Currently does it at ca. 10 kHz • Slave CAN controllers • Generate PWM for up to 3 motors • Interface local sensors • Can have local control algorithms
The set of local controllers • 7 slaves controllers for joints and sensors • 1 master controller • Interfaces slave controllers by CAN • Interfaces upstream system by RS232
Local control boards • All master and slave boards have a common base upon which a piggy-back unit can add I/O (sensors, additional communications, etc.)
Examples of piggy-back boards • Accelerometers • Strain gauges conditioning • Serial COM for master
First humanoid motion • The robot is able to stand, lean on sides, for/backward • Primitive locomotion motions have been achieved
Low cost... How Low? • Servomotors • Big size: ~50 € x 14 -> 700 € • Smaller size: ~30 € x 8 -> 240 € • Miscellaneous electronic components • Total -> ~300 € • Aluminium gears and belts • Total -> ~300 € • Batteries • ~80 € x 4 -> ~320€ • Sensors (except camera) • Negligible (<100€) • Raw materials (steel, aluminium) • Negligible (<100€) • Total ~ €2000 • Excluding manufacturing and development costs (software, etc.) • Still missing: • Vision unit, central control unit (PC104+), lots of software...
On-going and open issues • Next concerns for the platform • Joint position feedback from dedicated sensor (not servo’s own!) • Safety issues to automatic cut of power on controller failure • Better adjustable tensors for belts • Selection and installation of central control unit (Embedded Linux) • Selection and installation of the vision unit (FireWire..?) • Research concerns • Localized/distributed control algorithms • Elementary Gait definition • ...
Hints for local control • The difficult relation between planning and stability opens the way to localised control • Minimal dependence on planned variables • Better adaptation to changing conditions (e.g., load, ground) • Force-based perception is the key issue: • Reaction forces • Joint torques / motor currents • What local control can do • Accept a global directive and act locally based on an associated rule. • Example: • Top order: keep standing immune to perturbations • Local rules: try to actuate the joints you control in order to keep force balance (e.g., try to have a distribution of forces as uniform as possible on the foot area)
Conclusions • A highly versatile platform is possible to be built with constrained costs and off-the-shelf components. • The distributed control architecture has shown several benefits: • Easier development • Easier debugging • Provides modular approaches • The generic local controller using piggy-back modules is a confirmation of the modularity • Local controller capabilities include the possibility of localised control based simply on local perception and global directives. • A prototype system has been built and the selected technological solutions ensure a platform for research • A huge field of research issues can be addressed, mainly on control, perception and other autonomous navigation matters.
Author’s Short Biography • Vítor Santos is Associate Professor at the Department of Mechanical Engineering of the University of Aveiro • He received his PhD from the University of Aveiro in 1994 … • His research interests include … Tel: +351 234 370 828 Email: firstname.lastname@example.org Fax: +351 234 370 953 http://www.mec.ua.pt • Filipe Silva is Assistant Professor at the Dept. of Electronics and Telecommunications of the University of Aveiro • He received his PhD in Electrical Engineering from the University of Porto in 2002; modelling and control of biped locomotion systems • His main research interests are centred in the areas of Humanoid Robotics and Healthcare Robotics Tel: +351 234 370 531 Email: email@example.com Fax: +351 234 370 545 http://www.ieeta.pt