Mr V S MahalingamDirectorCentre for Artificial Intelligence and RoboticsDRDO ComplexC V Raman NagarBangalore 560 093

Shri VS Mahalingam joined DRDO after obtaining his Bachelor’s degree in Engineering in the year1973 from the College of Engineering, Guindy, affiliated to Madras University. He had advancedtraining in Software Engineering at Indus Tech, Pittsburgh, USA, and obtained his master degreefrom Indian Institute of Technology, Kanpur. He has made outstanding contributions in the developmentof equipments like Multiplexer for Adaptive Delta Modulation (ADM) coded signals, FDM signalencryptor (named Broad Band Caddis), Radio Regenerator Unit, Digital Trunk Unit, ShelterisedCommand Post for PINAKA Weapon system, C3I system - Artillery Combat Command and ControlSystem and Command Information Decision support System that have found widespread usageamongst services. He has published more than 12 papers in various International and Nationalforum. He is one of the members of team which received the Agni Award for Excellence in SelfReliance in the year 2003. He received the Scientist of the Year Award in 2003.

Mobile Robotics - A DRDO Perspective

Mobile Robots are set to play a very major role in the realization of future battlefield platforms includingunmanned /autonomous air / ground /under water vehicles. A classical application of unmannedground vehicles has been the disposal of hazardous explosives. In the military context, the newgeneration of fast, agile mobile robots is expected to perform such hazardous tasks as well assurveillance, reconnaissance, logistics support and even enemy attack.

These modern new generation robots are required to be built with sophisticated on board “intelligence”to efficiently perform the above tasks. The intelligence component comprises of an integrated GPS,Image /video processing, Laser ranging etc and advanced algorithms embedded into an onboardcomputer.

A number of DRDO labs are working on different classes of tracked, wheeled under water andunmanned/autonomous vehicles.

MOBILE ROBOTICSMOBILE ROBOTICS‐‐A DRDO A DRDO PERSPECTIVEPERSPECTIVE

VS MAHALINGAMI E O AIDIRECTOR, CAIR

DRDODRDOBANGALORE

MAV08 AGRA INDIAMAV08          AGRA        INDIA

Mobile RoboticsMobile Robotics-- A DRDO PerspectiveA DRDO PerspectiveMobile RoboticsMobile Robotics A DRDO PerspectiveA DRDO Perspective

An Unmanned Ground Vehicle Programme

(UGVs), which form part of Mobile Robotics has

been conceived by DRDO to realize a family of y y

mobile platforms for the services for use in

hazardous conditions and in hostile

environment.

Classification of UGV’sClassification of UGV’sClassification of UGV sClassification of UGV s

CategoryCategory Category weightCategory weight Responsible agencyResponsible agencyCategoryCategoryNomenclatureNomenclature

Category weightCategory weight Responsible agencyResponsible agency

1Micro UGVs

<500gm CAIR, Bangloreg , g

2 Miniature UGVs < 50 kg CAIR, Bangalore

3 Small UGVs <500 kg R&DE(Engrs), Pune

4 Medium UGVs <25000 kg VRDE, Ahmednagar

5 Large UGVs >25000 kg CVRDE, Chennai

RolesRoles

R l Micro UGV Miniature UGV Small UGV Medium UGV Large UGV Roles Micro UGV (<500gm)

Miniature UGV (upto 50 kg)

Small UGV (upto 500 kg)

Medium UGV(500 to 25000 kg)

Large UGV (greater than 25000kg)

Urban Y Y Y Y -

Cross Country Y Y YCross Country - - Y Y Y

Surveillance - Y Y Y -

Reconnaissance Y Y Y Y -

Target Designation - - Y Y -Target Designation - - Y Y -

IED Handling - - Y - -

NBC Recce - - Y Y Y

Hazardous Material - Y Y Y -Hazardous Material Handling

Y Y Y

Mine Laying - - - Y -

Mine Detection - - Y - Y

Mine Breaching - - - - Y

Sacrificial Role - Y - - -

Offensive Role for Guns /RLs or Missile

- - - Y YGuns /RLs or Missile Launchers

Load Carrier - - Y Y Y

Enabling TechnologiesEnabling Technologies

V hi l Pl tf• Vehicle Platform– Automatic Transmission– Electric Drives– Stabilization

E b dd d C t l• Embedded Control• Localization

– GPS, INS, Odometer• Perception

R LASER WR– Range sensors: LASER, mmWR– Image sensors: CCD, CMOS Cameras, Thermal Imagers

• Path Planning– Global

i i f ti GIS S t llit i• a priory information: GIS, Satellite images• Path optimization

– Local• Real time sensor data interpretation

T i d lli• Terrain modelling• Obstacle characterization• Obstacle avoidance algorithms

• Remote Control StationCommunication link– Communication link

– Software protocol– Man-machine interface– Data visualization

Advance Technology Development Advance Technology Development effortseffortseffortsefforts

• High Energy Density Rechargeable Batteries  (R&DE , g gy y gPune)

• Vision Link and Image Processing, mmWR(DEAL, Dehradun)

• Sensor Fusion, Path Planning, Intelligent Control, Autonomous navigation (CAIR, Bangalore)

• Role based specific sensor development (IRDE, Dehradun)

On Going DevelopmentsOn Going Developments

Project Lab

A d l f f l i l d & EAutomated Platform for Multi‐Purpose Payloads [AMPMP]

R&DE

Multi‐Sensor Land Mine Detection System [MLDS] R&DE, DLJ 

Unmanned Ground Vehicle for Surveillance and NBC Recce Role  [UGVSR]

VRDE

Re otely O e ated T a ked Vehi le[ROTV] CVRDERemotely Operated Tracked Vehicle[ROTV]  CVRDE

Miniature UGV [MINI‐UGV] CAIR

Mi M lti R b t [MICMR] CAIRMicro Multi‐purpose Robot [MICMR] CAIR

Unified Protocol Development [UPD] R&DE

Intelligent WheelchairIntelligent Wheelchair

• Control Modes– Joystick control, – Tape tracking, Wi l t t l– Wireless remote control

• 100 kg payload• 8 hrs continuous operation on single p gcharge

• Zero radius turning• ToT with• ToT with

– MTAB, Chennai– Keltron, Alappuzha– 515 Army Base Workshop, Bangalore

Mobile ManipulatorMobile Manipulator

• 2‐DOF wheeled base• 2‐DOF wheeled base

• 4‐DOF Articulated robot arm

P ll l fi i• Parallel‐finger gripper

• Camera with tilt control

• Wireless control

LeggedLegged--Wheeled Hybrid RobotWheeled Hybrid Robot

Rough terrain mobility by passive adaptation to ground profile

• Six actuated wheels

• Passively articulating Legs

• Weight: 30Kgs Payload: 20 Kgs• Weight: 30Kgs, Payload: 20 Kgs

• Modular motion controller

• 24V, 7.2 Ah Battery, (2 hrs endurance)y

• Wireless Joystick control (300 m)

LeggedLegged--Wheeled Hybrid Robot Wheeled Hybrid Robot contd..contd..

Stair-climbing Simulation Prototype-Iyp

Color TrackingColor Tracking

• Embedded Color camera • Real-time image processing• Embedded motion controller

Color camera

• Embedded motion controller• Move robot to keep object in

center of image

RC servomotor driven wheelsCapture:

Color Camera; CMOS for High speed (20 fps); Embedded

Image processing:Compression; High speed; Embedded

Tracking: Control algorithm; motion controller; motion

prediction

Articulated Tracked VehicleArticulated Tracked Vehicle

• 2 main tracks

• 2 active articulating tracks

• Uneven terrain mobility

• Wireless  link –data, video

St li biStep climbing sequence

Hexapod Walking Robot Hexapod Walking Robot (2(2--DoF Legs)DoF Legs)

• 6 legs, each 2 DoF6 egs, eac o

• Distributed Controller

– Leg controllersg

– Master control for gait

• IR remote control

• Obstacle avoidance‐

– IR proximity, 

– Touch sensors

Hexapod Walking Robot Hexapod Walking Robot (3(3--DoF Legs)DoF Legs)

• 3‐DoF Leg 5 bar linkage mechanism– 5‐bar linkage mechanism

• Omni‐directional motion• Leg kinematics with polynomial approximationpp

Version1• 2 Kgs

Version 2• 250 grams• A li D l i t i l• Acrylic, Delrin material• Micro integrated motor• PCB as structural component• Lithium polymer batteries• Lithium polymer batteries

Hexapod Hexapod Walking Robot Walking Robot (self(self--righting)righting)

• Lateral and Longitudinal rolling• High maneuverability leg:

– 3 DoF leg– articulated leg; >180 degree

joint rangej g

• Weight Distribution: – Placement of motors– Placement of motors– lithium polymer batteries– Low CG design

Snake RobotSnake Robot

• Locomotion using wave propagation technique of snakes– 12 modular joints– Centralized controller– Snake & caterpillar locomotion– Cluttered environment and pipe inspectionp p p

SIMULATION MODEL

Robot Sentry Robot Sentry (ROBOSEN)(ROBOSEN)• Autonomous Navigation in Semi-

Structured Environment

• Continuous Video Feed via Pan-Tilt-Zoom Network Color Camera

• Autonomous Navigation in Semi-Structured Environment

• Continuous Video Feed via Pan-Tilt-Zoom Network Color Camera

• GPS and Stabilized Digital Compass for Localization

• Scanning Laser Range Finder forObstacle Avoidance

• GPS and Stabilized Digital Compass for Localization

• Scanning Laser Range Finder forObstacle Avoidance

Current Pos/HeadDesired PosLaser range data

Obstacle Avoidance

• WiFi Link for Command & Control

• Endurance typically 3 hours

Obstacle Avoidance

• WiFi Link for Command & Control

• Endurance typically 3 hours

User Interface: Remote Laptop/PC• Display: GPS Map of Environment, Location & Heading of the

Robot, Laser Range Data• Parameter and display settings

Control Modes

User Interface: Remote Laptop/PC• Display: GPS Map of Environment, Location & Heading of the

Robot, Laser Range Data• Parameter and display settings

Control Modes• Control Modes– Manual: by Keyboard/ Mouse– Autonomous:

• Computes shortest path to defined t t

• Control Modes– Manual: by Keyboard/ Mouse– Autonomous:

• Computes shortest path to defined t ttarget

• Moves autonomously with obstacle avoidance

target• Moves autonomously with obstacle

avoidance

Th k YThank You

director@cair.drdo.in