This paper demonstrates that an adaptive computing system (ACS) is a good platform for implementing robotic control algorithms. We show that an ACS can be used to provide both good performance and high dependability. An example of an FPGA-implemented dependable control algorithm is presented. The flexibility of ACS is exploited by choosing the best precision for our application. This makes it possible to reduce the amount of required hardware and improve the performance. Results obtained from a WILDFORCE emulation platform showed that even using 0.35 mm technology, the FPGA-implemented control algorithm has comparable performance with the software-implemented control algorithm in a microprocessor based on 0.25 mm technology. Different voting schemes are used in conjunction with multi-threading and hardware redundancy to add fault tolerance to the robotic controller. Error-injection experiments demonstrate that robotic control algorithms with fault tolerance techniques are orders of magnitude less vulnerable to faults compared to algorithms without any fault tolerant features.