A Greedy Strategy for Tracking a Locally Predictable Target among Obstacles

Target tracking among obstacles is an interesting class of motion planning problems that combine the usual motion constraints with robot sensors' visibility constraints. In this paper, we introduce the notion of vantage time and use it to formulate a risk function that evaluates the robot's advantage in maintaining the visibility constraint against the target. Local minimization of the risk function leads to a greedy tracking strategy. We also use simple velocity prediction on the target to further improve tracking performance. We compared our new strategy with earlier work in extensive simulation experiments and obtained much improved results

Authors

• Tirthankar Bandyopadhyay
• Yuanping Li
• Marcelo H. Ang
• David Hsu

Keywords

• Target tracking
• Robot sensing systems
• Motion planning
• Mobile robots
• Mechanical sensors
• Trajectory
• Mechanical engineering
• Computer science
• Senior citizens
• Security
• Greedy Strategy
• Path Planning
• Velocity Prediction
• Motion Constraints
• Robot Sensors
• Improve Tracking Performance
• Amount Of Time
• Growth Activity
• Shortest Path
• Maximum Velocity
• Line-of-sight
• Radial Direction
• Closest Point
• Velocity Estimation
• Environmental Knowledge
• Velocity Direction
• Tangential Direction
• Radial Component
• Tangential Components
• Gap Edge
• Target Velocity
• Range Edge
• Current Time Step
• Target Trajectory
• City Block
• Position Of The Robot
• Single Edge