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Peter Redgrave is a pioneering researcher at the intersection of neuroscience and robotics, best known for his groundbreaking work on the basal ganglia and action selection. His research has fundamentally shaped our understanding of how the brain resolves conflicts between competing motor systems, a concept he has both modeled computationally and implemented in robotic architectures. His most influential work, "Layered Control Architectures in Robots and Vertebrates" (1999, 206 citations), established a crucial bridge between Brooks' subsumption architecture in robotics and layered control systems in vertebrate brains. Redgrave's seminal contributions include developing the first embodied computational models of the basal ganglia, as demonstrated in his highly cited papers "A robot model of the basal ganglia" (2005, 178 citations) and "Computational models of the basal ganglia: from robots to membranes" (2004, 147 citations). These works provided the first concrete evidence that the basal ganglia's intrinsic circuitry could serve as a biological action selection mechanism. He also made significant contributions to the study of intrinsic motivation and open-ended learning, co-editing a Frontiers Research Topic on the subject (2014, 69 citations) and leading the IM-CLeVeR project on intrinsically motivated cumulative learning in robots. His work has accumulated over 740 citations, establishing him as a key figure in neurorobotics.