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Intelligent Robotics Introduction Thomas Hellstr öm Hellström Umeå Umeå University Sweden 1 © Thomas Hellström ““ROBOT” ROBOT” • Robot Industry Association (RIA): “A re-programmable, multi-functional manipulator designed to move material, parts, tools, or specialized devices through variable programmable motions for the performance of a variety of tasks”. • A machine able to extract information from its environment and use knowledge about its world to move safely in a meaningful and purposive manner. 2 © Thomas Hellström Two major types of robots Industrial robots - Operates on the factory floor (static, deterministic) - Normally fixed or restricted mobility - Performs actions independent of the environment Mobile robots - Operates in “the real world” (dynamic, non deterministic) - Moves around - Acts through close interaction with the environment 3 © Thomas Hellström This course will be about: • “Mobile robots” • “Intelligent robots” • “Autonomous robots” • We will focus on Algorithms, Behaviour and Sensors, not so much on physical design 4 © Thomas Hellström What are they made of ? Computer (“brain”) Sensors – distance meters – “bumpers” – cameras Actuators – “locomotion” (moves the robot). Usually wheels, legs or tracked – Manipulation (affect other objects) gripper, “hand”, screwdriver,... 5 © Thomas Hellström Why Robots? The 3 D’s: 1. Dirty Money to make 2. Dull 3. Dangerous 6 © Thomas Hellström Typical applications Manufacturing •Spot or arc welding •Die casting •Surface coating •Assembly •Glueing •Sealing •Acid dipping … Other • Cleaning pipes and pools • • • • • Rescue robots Nuclear power plants Space expeditions Bomb disposal De-mining (>100 Million land mines in the world ) 7 © Thomas Hellström S ervice Robots Service (Dull?) • Helping elderly/handicapped • Post delivery • Vacuum cleaning • Lawn mowing 8 © Thomas Hellström k Ok, so you don’t want robots in the house… USC surgeons perform surgical with robotic assistance; No need for thoracotomy: splitting the chest between the ribs Hopefully beyond all of the 3 D’s 9 © Thomas Hellström Rotundus a swedish robot A sealed ball with no external moving parts. To move: the pendulum is lifted in the direction of travel, the centre of mass gets displaced and the ball starts rolling. To turn: Move the pendulum to either side. 10 © Thomas Hellström Research robots 11 © Thomas Hellström The future of Robots 12 © Thomas Hellström The pre history of Robotics… Robotics… Psychology Psychology in the beginning of the previous century: Behaviorism, John Watson: The subject of study should be behaviors instead of mental mechanisms. Every behavior could be explained as stimulusresponse mappings. Early 1930: Tolman found that a rat is building a “cognitive map” of its environment. Modern psychology admits the necessity of internal representations. E.g.: psycho therapy 13 © Thomas Hellström The pre history of Robotics… Robotics… Cybernetics Developed by Norbert Wiener in the late 1940s A combination of biology, information science, control theory. Seeks to explain the principles behind control in both animals and machines 14 © Thomas Hellström 1953: Gray Walter’s tortoise – Seeking light – Head toward weak light – Back away from bright light – Turn and push (for obstacle avoidance) – Recharge battery 15 © Thomas Hellström The pre history of Robotics… Robotics… Artificial Intelligence Born August 1955: Dartmouth Summer research Conference Marvin Minsky: “[an intelligent machine] would tend to build up within itself an abstract model of the environment in which it is placed. If it were given a problem it could first explore solutions within the internal abstract model of the environment and then attempt external experiments”. Dominated AI and robot research for 30 years. 16 © Thomas Hellström The Classical AI Approach (the ””hierarcical hierarcical paradigm” ”) paradigm paradigm”) Method: “sense-plan-act” – – – – Interprete sensors Model the world Plan Execute the plan The components are FUNCTIONS: – Perception – Learning – Planning 17 © Thomas Hellström The Behavior Based Approach Brooks 1986, Braitenberg 1984, Walter 1953 The components are BEHAVIORS instead of functions. E.g: – Avoid obstacles ! – Explore ! – Follow the light ! Method: – Each behavior module is a “reflex agent” mapping inputs to outputs. (also called “reactive systems”) – “Behavior fusion” if contradictions occour. 18 © Thomas Hellström Braitenberg Valentino Braitenberg 1984: “Braitenberg Vehicles” Excitatory (+) and Inhibitory (-) connections between photocells and motors: Light aversive (“ fear”) 19 © Thomas Hellström Braitenberg Vehicles Light attracted (”aggresive”) 20 © Thomas Hellström Braitenberg Vehicles Approaches and stops at strong light (“ love”) 21 © Thomas Hellström Braitenberg Vehicles Approaches light, but always exploring (“ explorer”) 22 © Thomas Hellström Braitenberg Vehicles Add various non- linear connections between sensor and engines. Result: oscillatory behaviors 23 © Thomas Hellström Braitenberg Vehicles Add various non- linear connections between sensor and engines. Result: oscillatory behaviors 24 © Thomas Hellström Simulated versus Real robots ADVANTAGES: Experiments can be designed and repeated! We can stay at our beloved keyboard! (Accelerated execution time) No need to recharge the batteries or to repair Environment parameters can be modified: friction, graviation, temperature, physical laws DISADVANTAGES: Requires an accurate MODEL of the world ! We will solve a simplified problem :( 25 © Thomas Hellström Examples of tasks Simple: Not so simple: Avoid obstacles Wall following Light following Push things to the corner Collective behaviour Soccer Robot vacuum cleaner Robot waiter Planetary exploration Rescue robots 26 © Thomas Hellström Robotics is Multidisciplinary Classical AI Knowledge representation, Natural language processing, Planning, Searching, Perception Machine learning Model free techniques: Neural networks for modeling, Kohonen nets for clustering of sensor signals, Fuzzy logic for control, Genetic algorithms to make the robot “evolve” Computer Science Software engineering, Architectures Numerical methods Optimization, Parameter estimation in models 27 © Thomas Hellström Robotics is Multidisciplinary Neurophysiology Human control systems Ethology Animal behavior Psychology Human behavior Robotics Path planning, Map making, Obstacle avoidance, Tactile sensors,… 28 © Thomas Hellström Challenges Perception - Limited, noisy sensors - Too much data / Hard to know what to care about Control - Limited capabilities of robot actuators/effectors - Power consumption/support Thinking - Lots of unsolved problems Environments - Dynamic, impose fast reaction times 29 © Thomas Hellström