
Algorithmic Foundations of Robotics XVI, Volume 1
Description
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This book is the first volume of two that present research advances on algorithmic robotics written by leading experts in the field. Algorithms are a fundamental component of robotic systems: they control or reason about motion and perception in the physical world. They receive input from noisy sensors, consider geometric and physical constraints, and operate on the world through imprecise actuators. The design and analysis of robot algorithms therefore raises a unique combination of questions in control theory, computational and differential geometry, computer science and machine learning. Advances in this area have a wide range of applications in manufacturing, computational biology, medical robotics, sensor networks, human-robot interaction, virtual environments, and many other areas.
These results were presented at the 16th edition of the International Workshop on the Algorithmic Foundations of Robotics (WAFR) held October 7-9, 2024 at the University of Illinois Discovery Partners Institute in the City of Chicago, Illinois, USA. This edition of WAFR also marked 30 years since its creation in 1994 as a small workshop. Since then, WAFR has established a reputation of being one of the most important venues for presenting cutting-edge research on algorithmic problems in robotics.
Each of the 47 chapters in these two volumes presents an exciting contribution in algorithmic robotics spanning motion and task planning, geometry, multi-robot systems, game theoretic algorithms, control, reinforcement learning, robot design and dynamics, planning with beliefs, minimalism, manipulation, planning with ``interesting'' goals, and perception, localization, and communication.
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Content
Hybrid Declarative-Imperative Representations for Hybrid Discrete-Continuous Decision-Making.- Towards Practical Finite Sample Bounds for Motion Planning in TAMP. Fast and Certifiable Trajectory Optimization.- Multi-Query Shortest-Path Problem in Graphs of Convex Sets.- GCS*: Forward Heuristic Search on Implicit Graphs of Convex Sets.- Leveraging Fixed-Parameter Tractability for Robot Inspection Planning.- Topology-Driven Recovery Path Planning in Dynamic Obstacle Environments.- SPITE: Simple Polyhedral Intersection Techniques for Motion Planning in Modified Environments.- Quad-tree Based Collision Detection for Scalable Multi-Robot Motion Planning.- Theory and Explicit Design of a Path Planner for an SE(3) Robot.- Geodesic turnpikes for robot motion planning.- Inverse Risk-sensitive Multi-Robot Task Allocation.- Tractability Frontiers in Multi-Robot Coordination and Geometric Reconfiguration. Group-Control Motion Planning Framework for Microrobot Swarms in a Global Field.- Anticipating Oblivious Opponents in Stochastic Games.- Auto-Encoding Bayesian Inverse Games.- Online state vector reduction during model predictive control with gradient-based trajectory optimisation.- From Pixels to Torques with Linear Feedback.- Interaction-aware Conformal Prediction for Crowd Navigation.- RAnGE: Reachability Analysis for Guaranteed Ergodicity.- Reparametrization of 3D CSC Dubins' Paths Enabling 2D Search.- Equivariant Action Sampling for Reinforcement Learning and Planning.- MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety.
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