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This paper discusses hardware and software improvements to the RoboSimian system leading up to and during the 2015 DARPA Robotics Challenge (DRC) Finals. Team RoboSimian achieved a 5th place finish by achieving 7 points in 47:59 min. We present an architecture that was structured to be adaptable at the lowest level and repeatable at the highest level. The low‐level adaptability was achieved by leveraging tactile measurements from force torque sensors in the wrist coupled with whole‐body motion primitives. We use the term “behaviors” to conceptualize this low‐level adaptability. Each behavior is a contact‐triggered state machine that enables execution of short‐order manipulation and mobility tasks autonomously. At a high level, we focused on a teach‐and‐repeat style of development by storing executed behaviors and navigation poses in an object/task frame for recall later. This enabled us to perform tasks with high repeatability on competition day while being robust to task differences from practice to execution.

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The hardware used for software implementation on a physical system introduces uncertainty into the controller. If neglected during design, this uncertainty can lead to poor controller performance, resulting in significant design and verification iterations. In this work, the effect of sampling time, quantization, and fixed-point computation are directly accounted for in the control design. Sampling time is compensated for by a discrete-time controller. A generic methodology is developed for modeling the worst-case scenario effect of quantization and fixed-point computation on the control commands. The cold-start emission control problem is used as a case study, and a discrete-time sliding surface controller is developed. Verification is performed to ensure the estimated worst-case scenario uncertainty bounds are accurate. The bounds are incorporated into a modified version of the control laws. During simulation the modified controller demonstrates significant reduction in tracking error in the presence of hardware imprecisions.