PPT-Safe Path Planning for an Autonomous Agent in a Hostile Env

Aka SAVE PACMAN Cyber Physical Systems Jimit Gandhi and Astha Prasad OUTLINE Inspiration Related Work Basic Model Model Extensions Safety Methodology Hybrid game extension Future Work. stanfordedu Sebastian Thrun Computer Science Department Stanford University Stanford CA 94305 thrunaistanfordedu Michael Montemerlo Computer Science Department Stanford University Stanford CA 94305 mmdeaistanfordedu James Diebel Computer Science Depa for Adaptive Sampling Using Mixed Integer. Linear Programming. A discussion on. Key words in title…... Path Planning. Autonomous Underwater Vehicles. Adaptive Sampling. Mixed Integer Linear programming. defining me agent tly. Autonomous exuon is clrly ntral to agency.The AIMA Agent [Ruell and Norvig 1995, page ] "An agent is ything that can be viewedas periving s envirment through sensors and acthat Wesley Chu. With slides taken from Armin . Hornung. Humanoid Path Planning. Humanoids have large number of DOF. Planning full body movements not computationally feasible. Alternative: plan for footstep locations, and use predefined motions to execute on these footsteps. Core:. Recapped . our general planning . strategy . that does a coarse space-time decoupled planning, followed by a . focused spatiotemporal . trajectory search. Extended our prior work to apply edge-augmented graph search to approximate the underlying path smoothing and nudging optimizations (continuous) that are needed for autonomous on-road . Core:. Developed a motion planner for on-road swerve . maneuvers. Developed a reinforcement learning (RL) formulation that learns human driving . patterns . in simulation . playback. Recorded human driving . Southern Nevada Fire Operations (SNFO). SNFO Hostile MCI Policy. In 2011 the Clark County Fire Department was like most first response agencies across the U.S. when it came to responding to an active shooter situation.. Peter van der Spuy. 1. THE THREATS. Routine response ?. We tend to down play the severity of the incident as a result of frequency and complacency (Domestic violence,stabbings,suicide). Changing times and increase in violent attacks on emergency personal. Design and Analysis of Hybrid Systems. Spring 2018. CS 599.. Instructor: Jyo Deshmukh. Acknowledgment: Some of the material in these slides is based on the lecture slides for CIS 540: Principles of Embedded Computation taught by Rajeev Alur at the University of Pennsylvania. . Decision-making and planning. Spring 2018. CS 599.. Instructor: Jyo Deshmukh. Decision-making hierarchy. Motion planning. Overview. 2. Decision-making hierarchy. 3. Route Planning. Behavioral Planning. Rahul Kala. Introduction. rkala.99k.org. Autonomous Vehicles. rkala.99k.org. Software Architecture. Sensor. Environment understanding. Sensor fusion. Localization. Planning. Control. Motion. Map. Mission. Rahul Kala. Introduction. rkala.99k.org. Autonomous Vehicles. rkala.99k.org. Software Architecture. Sensor. Environment understanding. Sensor fusion. Localization. Planning. Control. Motion. Map. Mission. A*. It . applies to . path-planning problems on known finite graphs whose edge costs increase or . decrease over . time. (Such cost changes can also be used to model edges or vertices that are . added or . Goals. What is an agent-based model. ?. Why . construct agent-based models. ?. What are the parts of an agent-based model?. How does one construct agent-based models?. What is an agent-based model?. What is an agent-based model?.