Multi-Robot Teamwork Cooperative Multi-Robot Systems
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1 Multi-Robot Teamwork Cooperative Lecture 1: Basic Concepts Gal A. Kaminka
2 2 Why Robotics? Basic Science Study mechanics, energy, physiology, embodiment Cybernetics: the mind (rather than the brain) Applied Science (Engineering) Humanist: Machines should be cheaper than people Pragmatist: Machines can be better than people Futurist: In 30 years, not enough people in west
3 3 The scientific problem chooses you. You don t choose it. -- Allen Newell, a founder of Artificial Intelligence (AI) My Scientific Problem: The Nature of the Mind What are the basic mechanisms that allow the mind to reason about, and interact with, a world?
4 What is a robot? Give me a few examples. Robot Is a rock a robot? 4
5 What is a robot? A toy spring car can move and act. Robot Actuators (Effectors) a robot can sense. 5
6 What is a robot? A sorting algorithm senses and acts. Robot Actuators (Effectors) Sensors a robot is persistent. 6
7 What is a robot? What about a remote alarm? Robot Actuators (Effectors) Sensors a robot is situated in an environment. 7
8 What is a robot? We re missing something here. Robot Actuators (Effectors) Sensors Environment a robot is responsive. 8
9 What is a robot? We re missing something here. Robot Sensors Process Actuators (Effectors) Environment a robot is responsive. 9
10 Here s what we have so far Robots: Are persistent with respect to their environment Sense and act Sense/act within the same environment (situated) Respond to senses using action Robot Environment 10
11 Here s what we have so far Robots: Are persistent with respect to their environment Sense and act Sense/act within the same environment (situated) Respond to senses using action Robot Environment 11
12 Why investigate robots? Because we want to understand how to build them. So that they do things for us. So that we can do other things instead. In other words, We are studying robotics because we are lazy. 12
13 The Agent/Environment/Task Framework Robot Environment Task 13 We want the robot to do tasks for us (or for itself) Therefore, it must take a task into account
14 In this course we focus on physical environments Agents are embodied Sensing and acting with uncertainty 14 Part of the environment is their own body Slippery grips, sensing is inaccurate Environment is dynamic, changes even without robot.
15 Characterizing Environments There are a number of characteristic dimensions: Dynamic vs. static Accessible vs. inaccessible 15 transparent vs. translucent Action Deterministic vs. non-deterministic Hidden vs. not hidden Discrete vs. continuous
16 Dynamic vs. Static Dynamic: Static: Environment changes even if agent takes no action Environment does not change until agent takes action Key question: Is the agent only cause of change in the environment? Physical environment is dynamic 16 Wind, other agents, continuous mechanical forces
17 Accessible vs. Inaccessible Accessible (transparent): Inaccessible (translucent): Agent can sense everything and anything. Nothing is hidden. Agent can only sense part of the environment. Some features of the environment are hidden. Key question: What can the agent sense about the environment? Physical environments typically inaccessible: 17 Cannot see behind you, nor over long distances, nor inside people.
18 Determinism Deterministic: Non-deterministic: An action results in a completely predictable change An action can result in one of a range of possible changes Uncertainty in the result Key question: If agent takes action, is it sure of the outcome? Physical environment is non-deterministic: 18 Slippery grasp, coin-flips, gambling
19 Hidden vs. not-hidden Hidden: sensors will report state with uncertainty Observations of state are not deterministic Not hidden: Sensing is perfect In physical environments: Sensors are never perfect 19 The inputs to the algorithm may be incorrect Only known probabilistically
20 Discrete or continuous? Discrete: Continuous: 20 Infinite possible values within a range Note: Actions or senses are clearly separated, limited number Different from discrete/continuous senses and actions Physical environments are continuous
21 Robots and Environments Many different environments can exist Different techniques are used with different environments We focus on techniques used in physical environments: 21 Dynamic, continuous, inaccessible, hidden, non-deterministic
22 Robot, Environment, and Task Robot Environment Task Given environment and task, how do we build a robot that carries out the task? 22
23 Robot Control In principle, our view is of an agent with three components: Actuators Sensors Think This view is sometimes referred to as sense-think-act cycle But this can be misleading: not necessarily so sequential Think Robot Sense Act Environment 23
24 Action Selection The action-selection problem (our focus): How to select action in real-time? How to select action that is good for task/goal? How to integrate competing needs of different subtasks? Depends on the capabilities of sense and act Think Robot Sense Act Environment 27
25 No one way to do things Many systems/techniques provide integrated solutions Multiple levels at which can be addressed: hardware, control, software, Example: better vision by blurring camera Example: using probabilistic inference to handle uncertainty Example: sensor placement affects behavior Robotics is a highly inter-disciplinary field. 28
26 29 Building Robots is HARD! (and therefore expensive, and slow) Materials are heavy or weak (and sometimes both) Motors and sensors are energy-greedy, often expensive Complexity, safety, reliability challenge programmers Hours of operation Falls on command Maximum lift: ~100s kilos minutes of operation Falls easily, and breaks easily
27 30 Still, useful.
28 31 Some (unknown) facts 1 out of 4 vacuum cleaners sold in Spain is a robot ~10 different brands robots currently in Afghanistan (+Iraq) Not including UAVs Delivery robots in more than 130 US hospitals Kiva Systems sold to Amazon, for $776,000,000
29 32 2 / 2 6 / 1 3
30 36 No robot is an island Always have others around them Human user/operator, bystanders, other robots People expect socially-smart robots Anthropomorphize robots (take them on vacation!) Reasons for multi-robot teams: Better range and use of batteries (e.g., in lawns) Can do things that cannot be done by one (e.g., push) Can succeed even if some members fail
31 Canonical Multi-Robot Team Tasks Patrolling Formation Coverage Foraging Box pushing Exploration Delivery
32 Q? 41
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