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Safe autonomy is important in many application domains, especially forapplications involving interactions with humans. Existing safe controlalgorithms are similar to one another in the sense that: they all providecontrol inputs to maintain a low value of an energy function that measuressafety. In different methods, the energy function is called a potentialfunction, a safety index, or a barrier function. The connections and relativeadvantages among these methods remain unclear. This paper introduces a unifiedframework to derive safe control laws using energy functions. We demonstratehow to integrate existing controllers based on potential field method, safe setalgorithm, barrier function method, and sliding mode algorithm into thisunified framework. In addition to theoretical comparison, this paper alsointroduces a benchmark which implements and compares existing methods on avariety of problems with different system dynamics and interaction modes. Basedon the comparison results, a new method, called the sublevel safe setalgorithm, is derived under the unified framework by optimizing thehyperparameters. The proposed algorithm achieves the best performance in termsof safety and efficiency on the vast majority of benchmark tests.

Safe Control Algorithms Using Energy Functions: A Unified Framework, Benchmark, and New Directions