IISc Guidance, Control and Decision Systems Laboratory

Last updated

Mobile Robotics Laboratory
Type Public
Established2002
Location
Campus Indian Institute of Science
Website guidance.aero.iisc.ernet.in/robotics/index.html

The Guidance, Control and Decision Systems Laboratory (GCDSL) is situated in the Department of Aerospace Engineering at the Indian Institute of Science in Bangalore, India. The Mobile Robotics Laboratory (MRL) is its experimental division. They are headed by Dr. Debasish Ghose, Full Professor. [1]

Contents

GCDSL was established in 1990 (the MRL in 2002) and is considered as one of the leading robotic research centers in India. GCDSL/MRL has close research collaborations with eminent academic groups in countries such as USA, UK, Israel, South Korea etc. It also has multiple Industry project grants.

Research overview

GCDSL was started with the primary aim of performing research in the fields of Swarm robotics, Multi-Robot Systems and Cooperative Robotics with applications to tasks such as cooperative transportation, robotic formations, cooperative search/rescue, and odor source localization. in MRL, several robotic platforms have been built in-house and used for real-world-experiments in order to validate algorithms related to some of the above research problems.

The group is dedicated towards creating intelligent systems that are able to autonomously operate in complex and diverse scenarios. They are interested in the mechatronic design and control of vehicles that efficiently adapt to different situations and perform in dynamic environments. This includes development of novel methods and tools for perception, mapping and path planning.

Over the years research has extended in the fields of Simultaneous Localization and Mapping (SLAM), Aerial Robotics and machine vision. Recently there's been an emphasis on computer vision and Machine learning for improving versatility and cognitive abilities of robotic platforms.

Current Projects

Mohamed Bin Zayed International Robotics Challenge (MBZIRC 2020)

The goal is that MBZIRC 2020 will be based on autonomous aerial and ground robots, carrying out navigation and manipulation tasks, in unstructured, outdoor and indoor environments. All the sub-challenges involve cooperation between multiple UAVs and swarm-abilities. These Challenges are (1) grip a swinging ball hanging from a fast-moving drone, (2) Three UAVs and one UGV has to pick up bricks and build a wall, (3) A set of four vehicles (3 UAV + 1 UGV) to douse a series of simulated fires in a high-rise building using a pressurized canister. These missions are at the frontier of Intelligent Aerial Robotics technology and are meant for real-world application. [2] The IISc-TCS team has been selected for an interim award of $100,000 (milestone prize i.e. stage-based). [3]

UAVs for Flood emergency response, aid planning and management (EPSRC), 2020

The project focuses on using UAVs to gather information about an unfolding flooding disaster, allowing emergency response units to prioritise resources and deploy them effectively. It will also address the challenges associated with flying UAVs in difficult situations, as well as how the data can be combined with accelerated flood inundation models to generate detailed evacuation plans, build community flood resilience, save lives and reduce economic damage. [4]

Interceptor Aerial Systems (Agile Pursuit of Target)

Archived Projects

Glowworm swarm optimization (GSO)

The glowworm swarm optimization (GSO) algorithm is an optimization technique developed for simultaneous capture of multiple optimums of multi-modal functions. [5] The algorithm utilizes agents called glowworms which use a luminescent quantity called Luciferin to (indirectly) communicate the function-profile information at their current location to their neighbors. The glowworm depends on a variable local-decision domain, which is bounded above by a circular sensor range, to identify its neighbors and compute its movements. Each glowworm selects a neighbor that has a Luciferin value more than its own, using a probabilistic mechanism, and moves towards it. These movements that are based only on local information enable the swarm of glowworms to split into disjoint subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple optimums (not necessarily equal) of a given multi-modal function. The algorithm was tested on a custom designed system of robots called Kinbots.

Histogramic intensity switching

Histogramic intensity switching (HIS) is a vision-based obstacle avoidance algorithm developed in the lab. It makes use of histograms of images captured by a camera in real-time and does not make use of any distance measurements to achieve obstacle avoidance. An improved algorithm called the HIS-Dynamic mask allocation (HISDMA) has also been designed. The algorithms were tested on an in-house custom built robot called the VITAR.

Multi-Robot simultaneous localization and mapping (SLAM)

Implementation of occupancy grid mapping using a miniature mobile robot equipped with a set of five infrared based ranging sensors is explored in this research. Bayesian methods are used to update the map. Another variant of this technique will utilize a single IR-range sensor to obtain range to different distinctive features in the surrounding environment and utilize the readings obtained to make the SLAM converge. These techniques will be extended to a swarm of robots. These robots would communicate using the ZigBee protocol among themselves and with a global coordinator (PC) which would be responsible for map merging. Simulation experiments are being carried out using the Player/Stage software. The robotic platform is built using a custom designed set of swarm robots called Glowworms.

Quad-rotor and Aerial Manipulator Test-bed

A quadrotor micro-air-vehicle (MAV) is a rotor-based craft with four rotors, usually placed at the corners of a square frame. The four motor speeds (and hence thrusts) are the control inputs which result in motion of the quadrotor. The dynamics of this vehicle are fast and highly coupled, and hence presents a challenging control problem. [6]
A quadrotor and control test-bed has been fabricated in-house at the Mobile Robotics Lab. Experiments on control are being conducted on the quadrotor, beginning with yaw, pitch and roll stabilization.

Robots developed in-house

Kinbots

A robotic platform consisting of four wheeled-mobile robots have been developed in the lab for multi-robot testing. They are similar in principle to Braitenberg Vehicles and use simple perception/interaction/actuation techniques to achieve individual vehicle complexity and produce effective group behavior through cooperation. These robots have been used to test out the GSO algorithm

Glowworms

These miniature robots are developed based on Kinbots. [5]

VITAR

VITAR (Vision based Tracked Autonomous Robot) consists of a tracked mobile robot equipped with a pan-tilt mounted vision sensor, an onboard PC, driver electronics, and a wireless link to a remote PC. It has been utilized to test vision based algorithms such as the HIS and the HIS-DMA.

Related Research Articles

Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.

An autonomous robot is a robot that acts without recourse to human control. Historic examples include space probes. Modern examples include self-driving vacuums and cars.

<span class="mw-page-title-main">Boids</span> Artificial life program

Boids is an artificial life program, developed by Craig Reynolds in 1986, which simulates the flocking behaviour of birds, and related group motion. His paper on this topic was published in 1987 in the proceedings of the ACM SIGGRAPH conference. The name "boid" corresponds to a shortened version of "bird-oid object", which refers to a bird-like object. Reynolds' boid model is one example of a larger general concept, for which many other variations have been developed since. The closely related work of Ichiro Aoki is noteworthy because it was published in 1982 — five years before Reynolds' boids paper.

<span class="mw-page-title-main">Micro air vehicle</span> Class of very small unmanned aerial vehicle

A micro air vehicle (MAV), or micro aerial vehicle, is a class of man-portable miniature UAVs whose size enables them to be used in low-altitude, close-in support operations. Modern MAVs can be as small as 5 centimeters - compare Nano Air Vehicle. Development is driven by commercial, research, government, and military organizations; with insect-sized aircraft reportedly expected in the future. The small craft allow remote observation of hazardous environments or of areas inaccessible to ground vehicles. Hobbyists have designed MAVs for applications such as aerial robotics contests and aerial photography. MAVs can offer autonomous modes of flight.

<span class="mw-page-title-main">Simultaneous localization and mapping</span> Computational navigational technique used by robots and autonomous vehicles

Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. While this initially appears to be a chicken or the egg problem, there are several algorithms known to solve it in, at least approximately, tractable time for certain environments. Popular approximate solution methods include the particle filter, extended Kalman filter, covariance intersection, and GraphSLAM. SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality.

<span class="mw-page-title-main">Swarm robotics</span> Coordination of multiple robots as a system

Swarm robotics is an approach to the coordination of multiple robots as a system which consist of large numbers of mostly simple physical robots. ″In a robot swarm, the collective behavior of the robots results from local interactions between the robots and between the robots and the environment in which they act.″ It is supposed that a desired collective behavior emerges from the interactions between the robots and interactions of robots with the environment. This approach emerged on the field of artificial swarm intelligence, as well as the biological studies of insects, ants and other fields in nature, where swarm behaviour occurs.

<span class="mw-page-title-main">Unmanned ground vehicle</span> Type of vehicle

An unmanned ground vehicle (UGV) is a vehicle that operates while in contact with the ground without an onboard human presence. UGVs can be used for many applications where it is inconvenient, dangerous, expensive, or impossible to use an onboard human operator. Typically, the vehicle has sensors to observe the environment, and autonomously controls its behavior or uses a remote human operator to control the vehicle via teleoperation.

<span class="mw-page-title-main">Mobile robot</span> Type of robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering.

A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers or wireless access points. Instead, each node participates in routing by forwarding data for other nodes. The determination of which nodes forward data is made dynamically on the basis of network connectivity and the routing algorithm in use.

<span class="mw-page-title-main">Webots</span> Open-source robot simulator

Webots is a free and open-source 3D robot simulator used in industry, education and research.

<span class="mw-page-title-main">Open-source robotics</span> Open-source branch of robotics

Open-source robotics is a branch of robotics where robots are developed with open-source hardware and free and open-source software, publicly sharing blueprints, schematics, and source code. It is thus closely related to the open design movement, the maker movement and open science.

<span class="mw-page-title-main">MikroKopter</span> German UAV manufacturer

MikroKopter is a German company, a subsidiary of HiSystems GmbH, that manufactures battery-powered radio-controlled unmanned aerial vehicles. The company is located in Moormerland, Leer District, in Lower Saxony.

The Learning Applied to Ground Vehicles (LAGR) program, which ran from 2004 until 2008, had the goal of accelerating progress in autonomous, perception-based, off-road navigation in robotic unmanned ground vehicles (UGVs). LAGR was funded by DARPA, a research agency of the United States Department of Defense.

<span class="mw-page-title-main">IRCF360</span>

Infrared Control Freak 360 (IRCF360) is a 360-degree proximity sensor and a motion sensing devices, developed by ROBOTmaker. The sensor is in BETA developers release as a low cost sensor for use within research, technical and hobby projects.

<span class="mw-page-title-main">Robotnik Automation</span> Spanish technology company

Robotnik Automation S.L.L. is a Spanish company that specializes in robot product development and robotics R&D projects. Robotnik is based in Valencia (Paterna) in Spain.

<span class="mw-page-title-main">National Robotics Engineering Center</span> Operating unit within the Robotics Institute of Carnegie Mellon University

The National Robotics Engineering Center (NREC) is an operating unit within the Robotics Institute (RI) of Carnegie Mellon University. NREC works closely with government and industry clients to apply robotic technologies to real-world processes and products, including unmanned vehicle and platform design, autonomy, sensing and image processing, machine learning, manipulation, and human–robot interaction.

An autonomous aircraft is an aircraft which flies under the control of on-board autonomous robotic systems and needs no intervention from a human pilot or remote control. Most contemporary autonomous aircraft are unmanned aerial vehicles (drones) with pre-programmed algorithms to perform designated tasks, but advancements in artificial intelligence technologies mean that autonomous control systems are reaching a point where several air taxis and associated regulatory regimes are being developed.

Debasish Ghose is a professor at Department of Aerospace Engineering, Indian Institute of Science. He is believed to have initiated work on cooperative control in India, having pioneered research on Intelligent control and multi-agents. He founded the first mobile robotics lab in India i.e. Mobile Robotics Laboratory at IISc in 2002. He is known for his early work in swarm intelligence, distributed computing and game theory. His primary research is in Guidance and control of autonomous vehicles, although, current interest is in Computational intelligence i.e. Machine Learning for Aerial Robotics.

<span class="mw-page-title-main">Margarita Chli</span> Greek computer vision and robotics researcher

Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping. Chli is also the Vice Director of the Institute of Robotics and Intelligent Systems and an Honorary Fellow of the University of Edinburgh in the United Kingdom. Her research currently focuses on developing visual perception and intelligence in flying autonomous robotic systems.

<span class="mw-page-title-main">Integrated Unmanned Ground System</span> Unmanned ground vehicle

Integrated Modular Unmanned Ground System (UGS or iMUGS) is a European Union's Permanent Structured Cooperation (PESCO) project that aims to create a European standard unmanned ground system and develop scalable modular architecture for hybrid manned-unmanned systems, as well as increasing interoperability, situational awareness and speeding up decision making. The project is coordinated by Estonia, with 10 other European countries participating. It will use Milrem's existing THeMIS unmanned ground vehicle for different payloads.

References

  1. "Aerospace Engineering, Indian Institute of Science, Bangalore" . Retrieved 25 January 2019.
  2. "Mohamed Bin Zayed International Robotics Challenge (MBZIRC)". Robert Bosch Centre for Cyber-Physical Systems. 8 August 2018. Retrieved 25 January 2019.
  3. www.ETtech.com. "TCS-IISc team chases million dollar drone prize - ETtech". ETtech.com. Retrieved 31 January 2019.
  4. "Debasish Ghose | Indian Institute of Science, Bengaluru | IISC | Department of Aerospace Engineering". ResearchGate. Retrieved 25 January 2019.
  5. 1 2 K.N. Krishnanand and D. Ghose, "Glowworm swarm based optimization algorithm for multi-modal functions with collective robotics applications," Multi-agent and Grid Systems, Issue 3, Volume 2, 2006, pp. 209 - 222.
  6. "Economic Times India reports on IISc-TCS robotics team". Robert Bosch Centre for Cyber-Physical Systems. 28 January 2019. Retrieved 31 January 2019.