Adam Pacheck

About

Adam Pacheck is a leading researcher at the intersection of formal methods and robotics, specializing in the automatic synthesis and repair of high-level robot behaviors. His work centers on using Linear Temporal Logic (LTL) to define complex tasks and then automatically generating correct-by-construction control policies. Pacheck’s major contributions include developing frameworks that can identify missing skills when a task is infeasible, as well as methods for the physically feasible repair of reactive tasks—allowing robots to adapt their capabilities to meet user specifications. His research also extends to social navigation, where he combines Satisfiability Modulo Theories (SMT) with human-robot interaction constraints to ensure socially acceptable robot motion. With over 30 citations across his most influential papers, Pacheck’s work is gaining traction for its practical approach to making formal verification accessible for real-world robotic systems. Notably, his 2023 paper on task repair has been recognized for its potential to streamline the development of robust, autonomous robots.

Research Focus

Key Achievements

Top Papers

1. 1
   Finding Missing Skills for High-Level Behaviors

   12 citations · 2020
2. 2
   Physically Feasible Repair of Reactive, Linear Temporal Logic-Based, High-Level Tasks

   9 citations · 2023
3. 3
   SMT-Based Control and Feedback for Social Navigation

   5 citations · 2019
4. 4
   Automatic encoding and repair of reactive high-level tasks with learned abstract representations

   4 citations · 2023
5. 5
   Automatic Encoding and Repair of Reactive High-Level Tasks with Learned Abstract Representations

   2 citations · 2022
6. 6
   Errors in Collective Robotic Construction

   2 citations · 2022

Key Collaborators

Contact & Links