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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2022)

Control barrier functions (CBFs) are one of the many used approaches for achieving safety in robot autonomy. This thesis tackles several challenges present in control barrier functions in different aspects, including optimization, control, planning and navigation.

This thesis is composed of three parts. In Part I, we point out the optimization infeasibility between CBF constraint and input constraint, and address the feasibility problem in optimal control for quadratic programming using control barrier functions under input constraints. We also notice that the potential conflict between input constraints and safety constraints also exists in the discrete-time domain together with model predictive control. This conflict is formally identified in reachability analysis and reachability is later enhanced in proposed formulations.

In the Part II, we focus on obstacle avoidance for control and trajectory generation in a tight environment, which requires polytopic obstacle avoidance. We analyze the optimization problem for obstacle avoidance between polytopes. The novel optimizations for obstacle avoidance in continuous domain and discrete-time domain are proposed to solve this challenge.

In Part III of the thesis, we discuss several applications of motion planning and navigation using control barrier functions.We firstly address the motion planning problem within a finite state machine which unifies a mid-level planner and a low-level safety-critical controller with application to autonomous driving. Next, we propose parallelism for motion planning with control barrier functions with application to autonomous racing. Finally, we explore the possibility of safety-critical motion planning for high dimensional systems such as Cassie, a life-size bipedal robot.

    Cover page: Challenges of Control Barrier Functions: Optimization, Control, Planning, and Navigation
    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2012)
    Continent-scale biogeography has been extensively studied in soils and marine systems, but little is known about biogeographical patterns in non-marine sediments. We used barcode pyrosequencing to quantify the effects of local geochemical properties and geographic distance for bacterial community structure and membership, using sediment samples from 15 lakes on the Tibetan Plateau (4-1670 km apart). Bacterial communities were surprisingly diverse, and distinct from soil communities. Four of 26 phyla detected were dominant: Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria, albeit 20.2% of sequences were unclassified at the phylum level. As previously observed in acidic soil, pH was the dominant factor influencing alkaline sediment community structure, phylotype richness and phylogenetic diversity. In contrast, archaeal communities were less affected by pH. More geographically distant sites had more dissimilar communities (r=0.443, P=0.030). Variance partitioning analysis showed that geographic distance (historical contingencies) contributed more to bacterial community variation (12.2%) than any other factor, although the environmental factors explained more variance when combined (28.9%). Together, our results show that pH is the best predictor of bacterial community structure in alkaline sediments, and confirm that both geographic distance and chemical factors govern bacterial biogeography in lake sediments.
      Cover page: Geographic distance and pH drive bacterial distribution in alkaline lake sediments across Tibetan Plateau
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