Meir Kalech

About

Meir Kalech is a prominent researcher specializing in fault detection and diagnosis in autonomous and robotic systems, with a particular focus on multi-robot coordination and anomaly detection. His work addresses one of the most critical challenges in modern robotics: ensuring that increasingly sophisticated autonomous machines can reliably identify and respond to faults before they cause harm or mission failure. Kalech's most influential contribution, "On Fault Detection and Diagnosis in Robotic Systems" (2018), has accumulated 141 citations and serves as a foundational reference in the field. His complementary survey on multi-robot fault diagnosis (2019, 67 citations) and his earlier work on online anomaly detection (2014, 92 citations) demonstrate a sustained commitment to advancing robustness in autonomous systems. Notably, his research spans both single-robot platforms and complex multi-agent environments, including unmanned vehicles and sensor-based diagnostics, reflecting remarkable breadth across the discipline. His earlier work on diagnosing coordination failures in distributed multi-robot systems using CSP algorithms (2006) highlights his long-standing engagement with the theoretical underpinnings of multi-agent systems. Across more than two decades of research, Kalech has made enduring contributions that bridge artificial intelligence, robotics, and systems engineering, making his work essential reading for anyone studying autonomous system reliability.

Research Focus

Key Achievements

Top Papers

1. 1
   On Fault Detection and Diagnosis in Robotic Systems

   141 citations · 2018
2. 2
   Online data-driven anomaly detection in autonomous robots

   92 citations · 2014
3. 3
   Fault Detection and Diagnosis in Multi-Robot Systems: A Survey

   67 citations · 2019
4. 4
   Online anomaly detection in unmanned vehicles

   34 citations · 2011
5. 5
   Sensor fault detection and diagnosis for autonomous systems

   29 citations · 2013
6. 6
   A sensor-based approach for fault detection and diagnosis for robotic systems

   28 citations · 2017
7. 7
   A hybrid approach for improving unsupervised fault detection for robotic systems

   24 citations · 2017
8. 8
   Diagnosis of multi-robot coordination failures using distributed CSP algorithms

   21 citations · 2006
9. 9
   A hybrid approach for fault detection in autonomous physical agents

   12 citations · 2014
10. 10
    Towards a Comprehensive Framework for Teamwork in Behavior-Based Robots

    7 citations · 2004

Key Collaborators

Contact & Links